PUBLICATIONS. Skewed reflected distributions generated by Laplace Kernel (with Woo and Pal). Austrian J. Statist., 38(1), To appear.
|
|
- Erick Terry
- 5 years ago
- Views:
Transcription
1 PUBLICATIONS Skewed reflected distributions generated by Laplace Kernel (with Woo and Pal). Austrian J. Statist., 38(1), To appear. Estimation of Pr(Y < X) when X and Y belong to different distribution families (with Pal and Woo). J. Prob. Statist. Sci., To appear. On Howell Tong s contributions to reliability. Special Volume edited by Kung-Sik Chan, World Scientific Publishing Company. 2009, To appear. Inference on reliability P(Y < X) in a truncated arcsine distribution (with J. Woo), Pak. J. Statist., To appear. Marginal distributions of crossing time and renewal numbers related with two-stage Erlang process (with M. Talpur and I. Zamir). J. Korean Data Inform. Sci. Soc, To appear. Two dimensional marginal distributions of crossing time and renewal numbers related with two-stage Erlang processes (with M. Talpur and I. Zamir). J. Mod. Appl. Statist. Meth., To appear. Some skew-symmetric reflected distributions (with Woo and Pal). Amer. J. Math. Mgmt. Sci., 28(24), 41-59, Stochastic orderings of integer valued random variables (with Woo, J. and Nadarajah, S.), Amer. J. Math. Mgmt. Sci., 28(24), , A comparison of methods of estimation of parameters of the Tukey s gh family of distributions (with M. Majumder). Pak. J. Statist., 24(2), , Some Skew-symmetric double inverted distributions (with Woo, Pal and Wahed). Intern. J. Statist. Sci., 7, 1-12, Generalized gamma variables with drought application (with Woo and Nadarajah). J. Korean Statist. Soc., 37, 37-45, Skewed reflected distributions generated by reflected gamma kernel (with Pal and Woo). Pak. J. Statist., 24(1), 77-86, A truncated bivariate generalized Pareto distribution (with Nadarajah). Comp. Commun., 30(8), , 2007.
2 On the ratio of Weibull random variables with dragline application, (with S. Nadarajah and S. Kotz), Intern. J. Industr. Engg., 24(1), 84-89, Pareto random variables for hydrological modeling, (with S. Nadarajah), Water Resources Managemant, DOI /s , Some exponentiated distributions (with Pal and Woo). Korean Commun. Statist., 14(1), , On the ratio of inverted gamma variates (with J. Woo and M. Pal). Austrian J. Statist., 36(2), , Information matrices for normal and Laplace mixtures (with S. Nadarajah). Inform. Sci., 177(3), , A truncated Pareto distribution (with S. Nadarajah). Comp. Commun., 30(1), 1-4, Skew-symmetric reflected distributions (with J. Woo). Soochow J. Math. 32(2), , Exponentiated Weibull distribution (with M. Pal and J. Woo). STATISTICA, LXIV, n.2, , Skew-symmetric reflected distributions (with J. Woo). Soochow J. Math. 32(2), , Bayesian multiple comparisons with nonparametric dirichlet process priors for negative binomial populations (with J. S. Cho and M. Begum), Pak. J.Statist., 22(2), 89-98, Nonparametric Bayesian multiple comparisons for dependence parameter in bivariate exponential populations (with J. S. Cho and M. Begum). J. Mod. App. Statist. Meth., 5(1), 66-72, The distribution of sums, products and ratios for Lawrance and Lewis's Bivariate exponential distribution (with S. Nadarajah), Comput. Statist. Data Anal., 50, , Parametric and non-parametric estimation for right-truncated exponential distribution (with J. Woo and S. Nadarajah), IAPQR Trans., Vol. 31(1), 47-55, Distribution of the ratio of generalized uniform variates (with J. Woo and M. Pal). Pak. J. Statist., 22(1), 11-19, 2006.
3 Bootstrapping Regression Residuals (with R. Imon). J. Korean Data Inform. Sci. Soc., 16(3), , Derivation of product and ratio of the elliptically symmetric Laplace distribution (with. S. Nadarajah). J. Statist. Stud., 25, 35-41, Nonparametric Bayesian multiple comparison for geometric populations (with J. S. Cho and M. Begum). J. Korean Data Inform. Sci. Soc., 16(4), , Inference on Reliability P(Y<X) in a p-dimensional Rayleigh distribution (with J. Woo). Math. Comp. Modell., 42, , Inference on reliability P(Y<X) in the Levy Case (with J. Woo). Math. Comp. Modell., 41, , On the ratio X/(X+Y) for Weibull and Levy distributions (with S. Nadarajah and J. Woo). J. Korean Statist. Soc. 34(1), 11-20, On the ratio of Weibull random variables (with S. Nadarajah). IAPQR Trans., 30(1), 43-51, On the ratio X/(X+Y) for the power function distribution (with J. Woo). Pak. J. Statist., 21(2), , Inference on P(Y < X) in a Pareto distribution (with J. Woo). J. Mod. Appl. Statist. Meth., 4(2), , On the characteristic function of the product of gamma and Rayleigh random variables (with S. Nadarajah). Calcutta Statist. Assoc. Bull., 57, Nos , , Estimation and testing of P(Y > X) in a two-parameter exponential distributions (with M. Pal and J. Woo). Statistics, 39(5), , Bayes estimators of the exponential distribution (with J. Woo and S. Nadarajah). J. Statist. Mgmt. Sys., 8(1), 53-58, Inference on P(Y < X) in a generalized uniform distribution (with M. Pal and J. Woo). Calcutta Statist. Assoc. Bull., 57 Nos , 35 48, Inference on reliability P(Y < X) in a power function distribution (with J. Woo). J. Statist. Mgmt. Sys., 8(3), , 2005.
4 Simultaneous identification of multiple outliers and high leverage points in linear regression (with R. Imon). J. Korean Data Inform. Sci. Soc., 16(2), , On the product and ratio of t and Laplace random variables (with S. Nadarajah). Pak. J. Statist., 21(1), 1-14, Information matrices for some bivariate gamma distributions (with S. Nadarajah). Inform. Sci., 34, 11-20, On the product of Laplace and Bessel random variables (with S. Nadarajah), J. Korean Data Inform. Sci. Soc., 15(4), , A Non-linear exponential (NLINEX) loss function in Bayesian Analysis (with AFM S. Islam and M. Roy). J. Korean Data Inform. Sci. Soc., 15(4), , Bayesian analysis of mean parameter in a Pareto distribution (with J. Woo). Calcutta Statist. Assoc. Bull., 55, On the product and the ratio of t and logistic random variables (with S. Nadarajah). Calcutta Statist. Assoc. Bull., 55, 1-14, Inference on reliability P(Y<X) in two-parameter exponential distribution (with J. Woo and M. Pal). Intern. J. Statist. Sci., 3, A skewed truncated t distribution (with S. Nadarajah). Mathematical and Computer Modelling, 40, , A conditional expectation method for improved residual estimation and outlier identification in linear regression (with Davies and Imon), Intern. J. Statist. Sci., 3, , Application of Bayesian Computational Techniques in Estimation of Posterior Distributional Properties of Lognormal Distribution (with Munni Begum). J. Korean Data Inform. Sci. Soc., 15(1), , Approximate estimation of the shape parameter in a standard gamma distribution (with J. Woo). J. Statist. Mgmt. Syst., 7(2), , Effects of an outlier for estimation in a uniform distribution (with J. Woo). J. Inform. Optim. Sci., 25(3), , 2004.
5 The mean and right-tail probability estimation in a Pareto distribution (with J. woo and G. Yoon). J. Statist. Mgmt. Syst., 6(1), 1-9, Efficient estimation of parameters of a uniform distribution in the presence of outliers (with U.J. Dixit and J. Woo). Soochow J. of Math., 29(4), , Estimation in an exponential distribution with common location and scale parameter (with J. Woo). Calcutta Statist. Assoc. Bull., 53( ), , On the lower and upper percentile values of the sphericity decision rule (with N. Saweris and H. Girgis). J. Korean Data Inform. Sci. Soc., 13(2), , Parametric estimation in the arcsine distribution (with J. Woo). Pak. J. Statist., 18(1), 71-76, On the use of Winsorized mean for truncated family of distributions under type II censoring (with A. Nanthakumar and K. Selvavel). J. Korean Data Inform. Sci. Soc., 13(1), , Skew-logistic distribution (with A.S. Wahed). J. Statist. Res., 35(2), 71-80, Dirac generalization function: An alternative to the change of variable technique (with S. Wahed). J. Statist. Res., 35(2), 57-70, Bayesian estimation of mean parameter in a standard power distribution (with J. Woo and G. Yoon). Data Analysis From Statistical Foundations: A Festschrift in Honour of D.A.S. Fraser's 75th Birthday (ed. A.K.Md.E. Saleh), Nova Science Publishers, Huntington, New York, , Right-tail probability estimation in the exponential model (with J. Woo and C. Lee). J. Inform. Optim. Sci., 22(2), , Bias reducing estimators in an exponential distribution (with J. Woo). Revista de Estadistica - Proceedings of the 23rd European Meeting of Statisticians, Vol. II, No.I, 35-36, Interval estimation for the mean and right-tail probability in a power function distribution (with J. Woo). J. Statis. Stud., 20, 37-39, The UMVUE for mean and right-tail probability in a standard power-function distribution (with J. Woo and G. Yoon). Estadistica, 52(158, 159), 1-10, Note on generalized power series distribution (with J. Woo). J. Statist. Stud., 20, 33-36, 2000.
6 Effects of an unidentified outlier for parametric estimation in a power function distribution (with J. Woo and G. Yoon). J. Statist. Res. (A Special Volume in Honour of the 80th Birthday of Professor C. R. Rao), 34(2), 91-98, Application of neural networks in aluminum corrosion (with J. Powers). J. Korean Data Inform. Sci. Soc., 11(2), , UMVUE for series in scale parameter of a gamma distribution (with J. Woo and S. Jean). J. Statist. Mgmt. Sys., 3(2), , MSE-Comparisons of Bayes reliability estimators in a Burr distribution. (with J. Woo). J. Inform. Optim. Sci., 21(2), , Jackknife parametric estimation in a truncated arcsine distribution (with J. Woo and C. Lee). Calcutta Statist. Assoc. Bull., 49( ), , Quintiles for Shapiro-Francis W' statistic (with M. Raman). J. Korean Data Inform. Sci. Soc., 10(1), 1-10, Right-tail probability estimation in a Burr distribution (with J. Woo). J. Statist. Res., 33(2), 51-55, Optimal Linear Inference Using Selected Order Statistics in Location-Scale Models (with D. Umbach). Handbook of Statistics Vol. 17: Order Statistics and Their Applications. eds. N. Balakrishnan and C. R. Rao. Elsevier Science Publishing, pages , Variances of the sample midrange and the sample median (with J. Woo). J. Statist. Stud., 18, 63-70, Some negative binomial mixture distributions (with M. K. Roy and S. K. Sunhat). J. Inform. Optim. Sci., 19(2), , Bayes estimation of Bernoulli parameter in restricted space (with J. Woo). J. Statis. Res., 32(1), 81-87, Conservative spacing for the Freshet distribution (with D. Umbach). J. Statist. Mgmt. Sys., 1(1), 1-9, Exterior and interior trimmed means in an exponential model (with J. Woo and C. Lee). J. Statist. Stud., 17, 13-20, On approximation of n-fold convolutions of mixtures of normal distributions (with Sergey Nagaev, Vladimir Chebotarev, and Anatolii Zolotukhin). Del'nevostochnyi matematicheskii
7 sbornik, 3, 23-48, Distributions of several multivariate test criteria in the canonical correlation case under violation (with N. Saweris). J. Statist. Plan. Infer., 62, , The jackknife quasi-ranges for a truncated arcsine distribution (with J. Woo). J. Statist. Res., 31(1), 35-41, Conservative spacings for the Weibull and extreme value distributions (with D. Umbach). Calcutta Statist. Assoc. Bull., 46, , A smooth goodness-of-fit test using selected sample quantiles (with Dale Umbach). J. Korean Statist. Assoc., 25(3), , Parametric estimation of two-parameter exponential model in the presence of unidentified outliers (with Jungsoo Woo). J. Inform. Optim. Sci., 17, 57-63, Parametric estimates in a generalized Pareto distribution (with Jungsoo Woo). J. Inform. Optim. Sci.,16, , Inference based on optimal spacing: Some recent results. Proc. ICCS IV, ,1994. Unified jackknife estimation for parameter changes in the exponential distribution (with Jungsoo Woo). J. Statist. Stud., 14, 20-23, Comparison of two estimations for population variance by concentrated criterion (with Jungsoo Woo). J. Statist. Stud., 14, 1-8, Estimating functions of the parameters of normal and logistic distributions using conservative spacings (with Dale Umbach). Pak. J. Statist., 10(1)A, , An asymptotically minimax procedure for selecting the $t$-best multinomial cells (with S. Bhandari). J. Statis. Plan. Inf., 38(1), 65-74, Statistical Education in Bangladesh. Proceedings of the Fourth International Conference on Teaching Statistics, Vol. 2, , An optimal sequential procedure for ranking pairwise compared treatments (with S. K. Bhandari and S. N. Hande). Calcutta Statist. Assoc. Bull., 43, , Binomial mixtures of some standard distributions (with M. Roy and A. Roy). J. Inform. Optim. Sci., 14(1), 57-71, 1993.
8 Conservative spacings for the estimation of location and scale (with D. Umbach). J. of Inform. Optim. Sci., 14(3), , Estimating functions of location and scale parameters (with E. Saleh and D. Umbach). Soochow J. Math., 19(3), , ASA survey of 1992 Chapter activities. Amstat News, No. 202, , Estimating life functions of chi distribution using selected order statistics (with D. Umbach and E. Saleh). IIE Transactions, 24(5), 88-98, A class of Poisson mixtured distributions (with M. Roy and S. Rahman). J. Inform. Optim. Sci., 13(2), , Estimation of quantiles using selected order statistics (with E. Saleh and K. Hassanein). Handbook of the Logistic Distribution, ed: N. Balakrishnan. Mercel and Dekker, New York , Impacts of equi-correlated responses on multicollinearity (with M. A. Ali). Commun. Statis. Theor. Meth., 21(7), , A goodness-of-fit test for the exponential distribution (with D. Umbach). Pak. J. Statist., B 7(3), 39-52, Dwyer functions D u and their applications to sampling without replacement from a finite population (with N. Mikhail). J. Statist. Res., 24, 41-65, Multivariate augmented factorial monomial symmetric functions (with N. Mikhail and R. Chasnov). J. Statist. Res., 24, 17-26, Three goodness-of-fit tests based on selected order statistics (with D. Umbach). Soochow J. Math., 16(1), 37-52, Non-linear estimation for the log-logistic distribution using selected order statistics (with D. Umbach). J. Statist. Stud., 10, 1-8, The distributions of some statistics associated with two multivariate hypotheses under violations in the complex case (with N. Saweris). Commun. Statist. Theor. Meth., 19(4), , Characterization of the exponential and Weibull distributions by conditional variance (with M.I. Beg). Pak. J. Statist. B, 5(3), , 1989.
9 A Shapiro-Wilk type goodness-of-fit test using a few order statistics (with D. Umbach). J. Statist. Plan. Inf., 22, , Estimation of quantiles of symmetrically truncated logistic distribution using a few selected order statistics (with D. Umbach). J. Inform. Optim. Sci., 10(2) , Estimation and testing of hypotheses about quantile functions of normal distribution (with E. Saleh and K. Hassanein). J. Inform. Optim. Sci., 9(1), 85-98, Linear estimation and tests of quantiles of logistic distribution based on selected order statistics (with E. Saleh and K. Hassanein). J. Inform. Optim. Sci., 9(3), , Tables of BLUE's for quantiles of symmetrically truncated logistic distribution (with D. Umbach). Mathematical Sciences Technical Report, No. 81, Ball State University, 26 pages, Characterization of probability distributions through higher order gap (with A. H. Khan). Commun. Statist. Theor. Meth., 16(5), , On order statistics from the log-logistic distribution (with A. H. Khan). J. Statist. Plan. Inf., 17, , Expressions of multivariate h-statistics in terms of power sums and sample moments (with N. Mikhail and R. Sears). J. Statist. Stud., 7, 1-7, The exact distribution of sample deviations from the K independent sample medians with applications (with N. Mikhail and L. Lester). J. Statist. Stud., 6, 1-7, Estimation of the parameters of the double exponential distribution using symmetric spacings (with D. Umbach and E. Saleh). Soochow J. Math., 12, , A goodness-of-fit test using optimal spacing (with D. Umbach). Proceedings of the Business and Economic Section of the American Statistical Association, pages , Tests of significance for the exponential distribution based on selected quantiles (with D. Umbach and E. Saleh). Sankhya B, 47, , Large sample estimation of Pareto quantiles using selected order statistics (with E. Saleh and D. Umbach). Metrika, 32, 49-56, 1985.
10 Testing Pareto quantiles using selected order statistics (with D. Umbach). J. Statist. Stud., 4, , Tests of significance using selected sample quantiles (with E. Saleh and D. Umbach). Statist. Probab. Lett., 2, , Hypothesis testing for double exponential distribution based on optimal spacing (with D. Umbach and E. Saleh). Soochow J Math., 10, , On the use of count data in estimation of the parameter of exponential distribution (with D. Umbach). Aligarh J. Statist., 3 and 4, 1-7, Estimation and tests of hypothesis for quantiles of normal distribution (with E. Saleh and K. Hassanein). Technical Report Series of the Laboratory for Research in Statistics and Probability, No. 32, Carleton University, Ottawa, Canada, Pages 1-20, Linear Estimation and tests of quantiles of logistic distribution based on selected order statistics (with E. Saleh and K. Hassanein). Technical Reports Series of the Laboratory for Research in Statistics and Probability, No. 32, Carleton University, Ottawa, Canada, pages 34-52, Departure from normality of Fisher's and Harley's transformations of the correlation coefficient (with N. Mikhail and P. Gatz). J. Statist. Stud., 3, 1-12, Simplified estimates of the parameters of the exponential distribution from samples censored in the middle (with E. Saleh and D. Umbach). Commun. Statist. Simula. Computa., 12, , Estimating quantiles using optimally chosen order statistics (with D. Umbach, E. Saleh, and K. Hassanein). Commun. Statist. Theor. Meth., 12(19), , Estimating the quantile function of location-scale family of distributions base on few selected order statistics (with E. Saleh and D. Umbach). J. Statist. Plan. Inf., 8, 75-86, Small sample quantile estimation of the exponential distribution using optimal spacings (with D. Umbach and E. Saleh). Sankhya B, 44, , Application of subset selection procedures to business: binomial and multinomial cases (with D. Umbach). Proceedings of the Midwest American Institute for Decision Sciences Annual Conference, Milwaukee, Wisconsin, 86-88, Use of order statistics in estimating exponential quantiles (with D. Umbach and K. Hassanein). Proceedings of the American Institute for Decision Sciences Annual Meeting, San
11 Francisco, CA, 2, , A note on estimating the mean of the negative exponential distribution using selected order statistics (with D. Umbach). Proceedings of the Business and Economics Section of American Statistical Association, pages , Small sample quantile estimation of Pareto population using two order statistics (with D. Umbach and K. Hassanein). Aligarh J. Statist., 1, , Small sample estimation of exponential quantiles with two order statistics (with D. Umbach and K. Hassanein). Aligarh J. of Statist, 1, , Estimation of quantiles of exponential and double exponential distributions based on two selected order statistics (with D. Umbach and K. Hassanein). Commun. Statist. Theor. Meth., A10(19), , Estimating Pareto quantiles using two order statistics (with D. Umbach and K. Hassanein). Commun. Statist.Theor. Meth., A10(19), , Unbiased estimates of the generalized variance for finite population (with N. Mikhail). J. Indian Statist. Assoc., 19, 85-92, Monte Carlo studies of some robust adaptive procedures for location (with F. Forst). Canadian J. Statist., 9(2), , An analytical decision model for evaluating a multi- product small business venture (with N. Ahmed). Proceedings of the Midwest American Institute for Decision Sciences Annual Meeting, Detroit, MI, , Application of subset selection procedures to business: The normal case (with D. Umbach and N. Ahmed). Proceedings of the Midwest American Institute for Decision Sciences Annual Meeting, Detroit, MI, , Interpreting sufficiency using partition (with L. Bookmyer and D. Umbach). J. Statist. Res., 15, 1-7, A collection of three papers on estimation of quantiles based on selected order statistics (with E. Saleh and D. Umbach). Carleton Mathematical Lecture Note, No. 35, Carleton University, Ottawa, Canada, 47 pages, Moments and product moments of the k- statistic, h-statistic, and l-statistic for infinite and finite populations (with N. Mikhail). J. Statist. Res., 14, 39-48, 1980.
12 Adaptive robust procedures as estimation technique for business data analysis (with F. Forst and N. Ahmed). Proceedings of the American Institute for Decision Sciences Annual Meeting, Las Vegas, Nevada, 2, , Application of ridge regression to sales forecasting (with B. Bulmahn and N. Ahmed). Proceedings of the Annual Meeting of the Midwest American Institute for Decision Sciences, Dayton, Ohio, , A linear robust adaptive procedure (with F. Forst). Mathematical Sciences Technical Reports, No. 35, Ball State University, 13 pages, Non-linear robust adaptive procedures (with F. Forst). Mathematical Sciences Technical Reports, No. 33, Ball State University, 14 pages, Bivariate moments and product moments of moment statistics for samples from finite populations for weight six (with N. Mikhail). J. Statist. Res., 13, 31-41, Ridge regression: Two applications (with B. Bulmahn). Mathematical Sciences Technical Reports, No. 26, Ball State University, 20 pages, Effect of ill-conditioned data on least squares estimator (with B. Bulmahn). Mathematical Sciences Technical Reports, No. 24, Ball State University, 20 pages, A note on complete sufficient statistics (with L. Bookmyer). Mathematical Sciences Technical Reports, No. 14, Ball State University, 3 pages, Partition approach to sufficiency (with L. Bookmyer). Mathematical Sciences Technical Reports, No. 13, Ball State University, 12 pages, Behavior of Student's ratio under nonstandard situations. Mathematical Sciences Technical Reports, No. 12, Ball State University, 29 pages, An alternative derivation of the distribution of correlation matrix. Mathematical Sciences Technical Reports, No. 11, Ball State University, 7 pages, Sampling from finite population and its application to k-statistics (with N. Mikhail). J. Statis. Res., 10(2), 77-84, An alternative method for approximating the potential and gradient at any point between an insulated cable to plane (with T. Lanoue). Mathematical Sciences Technical Reports, No. 5, Ball State University, 19 pages, 1976.
13 A mathematical method for approximating the potential and gradient at any point between an insulated cable to plane (with T. Lanoue and V. Boaz). Mathematical Sciences Technical Reports, No. 4, Ball State University, 15 pages, Moments of Dwyer's statistics and k-statistics and their products for finite and infinite sampling with application (with N. Mikhail). Proceedings of Statistics Days Conference, Ball State University, , Proceedings of Statistics Days, April 9-10, 1976 (ed), Mathematical Sciences, Ball State University, 142 pages, Tail distribution of ``Student's'' ratio for t greater than or equal to (n-2)/2 in samples from rectangular distribution. J. Statist. Res., 10(1), 43-71, On the exact distribution of Wilk's statistic in collinear case (with N. Mikhail). J. Statist. Res., 9(1), 39-50, Bivariate moments and product moments of moment- statistics for samples from finite population of size n (with N. Mikhail and C. Dwyer). J. Statist. Res., 9(2), 75-86, Tail distribution of Student's ratio for t greater than or equal to n-1 in samples of size n from a rectangular distribution. J. Statist. Res., 9(1), 11-24, Approximate estimates of the parameters of truncated gamma distribution (with N. Mikhail). J. Statist. Res., 8(2), 55-65, Distribution of Student's ratio for correlated observations. Statistische Hefte, International Zeitschrift fur Theorie Und Praxis, 4, , Distribution of correlation matrix (with D. A. S. Fraser and Y. S. Lee). Bull. Inst. Statist. Res. Train., (renamed J. Statist. Res.), 4(1), 1-15, Presentations, Sessions Chaired, Editorial Boards, Articles refereed and Reviewed Back to my home page
Stat 5101 Lecture Notes
Stat 5101 Lecture Notes Charles J. Geyer Copyright 1998, 1999, 2000, 2001 by Charles J. Geyer May 7, 2001 ii Stat 5101 (Geyer) Course Notes Contents 1 Random Variables and Change of Variables 1 1.1 Random
More informationPreface Introduction to Statistics and Data Analysis Overview: Statistical Inference, Samples, Populations, and Experimental Design The Role of
Preface Introduction to Statistics and Data Analysis Overview: Statistical Inference, Samples, Populations, and Experimental Design The Role of Probability Sampling Procedures Collection of Data Measures
More informationTABLE OF CONTENTS CHAPTER 1 COMBINATORIAL PROBABILITY 1
TABLE OF CONTENTS CHAPTER 1 COMBINATORIAL PROBABILITY 1 1.1 The Probability Model...1 1.2 Finite Discrete Models with Equally Likely Outcomes...5 1.2.1 Tree Diagrams...6 1.2.2 The Multiplication Principle...8
More informationCOPYRIGHTED MATERIAL CONTENTS. Preface Preface to the First Edition
Preface Preface to the First Edition xi xiii 1 Basic Probability Theory 1 1.1 Introduction 1 1.2 Sample Spaces and Events 3 1.3 The Axioms of Probability 7 1.4 Finite Sample Spaces and Combinatorics 15
More informationISI Web of Knowledge (Articles )
ISI Web of Knowledge (Articles 1 -- 18) Record 1 of 18 Title: Estimation and prediction from gamma distribution based on record values Author(s): Sultan, KS; Al-Dayian, GR; Mohammad, HH Source: COMPUTATIONAL
More informationContents. Preface to Second Edition Preface to First Edition Abbreviations PART I PRINCIPLES OF STATISTICAL THINKING AND ANALYSIS 1
Contents Preface to Second Edition Preface to First Edition Abbreviations xv xvii xix PART I PRINCIPLES OF STATISTICAL THINKING AND ANALYSIS 1 1 The Role of Statistical Methods in Modern Industry and Services
More informationSubject CS1 Actuarial Statistics 1 Core Principles
Institute of Actuaries of India Subject CS1 Actuarial Statistics 1 Core Principles For 2019 Examinations Aim The aim of the Actuarial Statistics 1 subject is to provide a grounding in mathematical and
More informationPATTERN RECOGNITION AND MACHINE LEARNING CHAPTER 2: PROBABILITY DISTRIBUTIONS
PATTERN RECOGNITION AND MACHINE LEARNING CHAPTER 2: PROBABILITY DISTRIBUTIONS Parametric Distributions Basic building blocks: Need to determine given Representation: or? Recall Curve Fitting Binary Variables
More informationIrr. Statistical Methods in Experimental Physics. 2nd Edition. Frederick James. World Scientific. CERN, Switzerland
Frederick James CERN, Switzerland Statistical Methods in Experimental Physics 2nd Edition r i Irr 1- r ri Ibn World Scientific NEW JERSEY LONDON SINGAPORE BEIJING SHANGHAI HONG KONG TAIPEI CHENNAI CONTENTS
More informationHANDBOOK OF APPLICABLE MATHEMATICS
HANDBOOK OF APPLICABLE MATHEMATICS Chief Editor: Walter Ledermann Volume VI: Statistics PART A Edited by Emlyn Lloyd University of Lancaster A Wiley-Interscience Publication JOHN WILEY & SONS Chichester
More informationContinuous Univariate Distributions
Continuous Univariate Distributions Volume 1 Second Edition NORMAN L. JOHNSON University of North Carolina Chapel Hill, North Carolina SAMUEL KOTZ University of Maryland College Park, Maryland N. BALAKRISHNAN
More informationTesting Statistical Hypotheses
E.L. Lehmann Joseph P. Romano Testing Statistical Hypotheses Third Edition 4y Springer Preface vii I Small-Sample Theory 1 1 The General Decision Problem 3 1.1 Statistical Inference and Statistical Decisions
More informationMoments of the Reliability, R = P(Y<X), As a Random Variable
International Journal of Computational Engineering Research Vol, 03 Issue, 8 Moments of the Reliability, R = P(Y
More informationStatistical Methods in HYDROLOGY CHARLES T. HAAN. The Iowa State University Press / Ames
Statistical Methods in HYDROLOGY CHARLES T. HAAN The Iowa State University Press / Ames Univariate BASIC Table of Contents PREFACE xiii ACKNOWLEDGEMENTS xv 1 INTRODUCTION 1 2 PROBABILITY AND PROBABILITY
More informationNotes on a skew-symmetric inverse double Weibull distribution
Journal of the Korean Data & Information Science Society 2009, 20(2), 459 465 한국데이터정보과학회지 Notes on a skew-symmetric inverse double Weibull distribution Jungsoo Woo 1 Department of Statistics, Yeungnam
More informationExperimental Design and Data Analysis for Biologists
Experimental Design and Data Analysis for Biologists Gerry P. Quinn Monash University Michael J. Keough University of Melbourne CAMBRIDGE UNIVERSITY PRESS Contents Preface page xv I I Introduction 1 1.1
More informationThe comparative studies on reliability for Rayleigh models
Journal of the Korean Data & Information Science Society 018, 9, 533 545 http://dx.doi.org/10.7465/jkdi.018.9..533 한국데이터정보과학회지 The comparative studies on reliability for Rayleigh models Ji Eun Oh 1 Joong
More informationPROBABILITY DISTRIBUTIONS. J. Elder CSE 6390/PSYC 6225 Computational Modeling of Visual Perception
PROBABILITY DISTRIBUTIONS Credits 2 These slides were sourced and/or modified from: Christopher Bishop, Microsoft UK Parametric Distributions 3 Basic building blocks: Need to determine given Representation:
More informationPART I INTRODUCTION The meaning of probability Basic definitions for frequentist statistics and Bayesian inference Bayesian inference Combinatorics
Table of Preface page xi PART I INTRODUCTION 1 1 The meaning of probability 3 1.1 Classical definition of probability 3 1.2 Statistical definition of probability 9 1.3 Bayesian understanding of probability
More information[1] Thavaneswaran, A.; Heyde, C. C. A note on filtering for long memory processes. Stable non-gaussian models in finance and econometrics. Math.
[1] Thavaneswaran, A.; Heyde, C. C. A note on filtering for long memory processes. Stable non-gaussian models in finance and econometrics. Math. Comput. Modelling 34 (2001), no. 9-11, 1139--1144. [2] Peiris,
More informationNotation Precedence Diagram
Notation Precedence Diagram xix xxi CHAPTER 1 Introduction 1 1.1. Systems, Models, and Simulation 1 1.2. Verification, Approximation, and Validation 8 1.2.1. Verifying a Program 9 1.2.2. Approximation
More informationAn Introduction to Multivariate Statistical Analysis
An Introduction to Multivariate Statistical Analysis Third Edition T. W. ANDERSON Stanford University Department of Statistics Stanford, CA WILEY- INTERSCIENCE A JOHN WILEY & SONS, INC., PUBLICATION Contents
More informationA Course in Statistical Theory
A Course in Statistical Theory David J. Olive Southern Illinois University Department of Mathematics Mailcode 4408 Carbondale, IL 62901-4408 dolive@.siu.edu January 2008, notes September 29, 2013 Contents
More informationFoundations of Probability and Statistics
Foundations of Probability and Statistics William C. Rinaman Le Moyne College Syracuse, New York Saunders College Publishing Harcourt Brace College Publishers Fort Worth Philadelphia San Diego New York
More informationTesting Statistical Hypotheses
E.L. Lehmann Joseph P. Romano, 02LEu1 ttd ~Lt~S Testing Statistical Hypotheses Third Edition With 6 Illustrations ~Springer 2 The Probability Background 28 2.1 Probability and Measure 28 2.2 Integration.........
More informationStatistical Inference : Consistency Unbiasedness
UPSC IFS Statistics Syllabus Paper - I Probability : Sample space and events probability measure and probability space random variable as a measurable function distribution function of a random variable
More informationA Note on Certain Stability and Limiting Properties of ν-infinitely divisible distributions
Int. J. Contemp. Math. Sci., Vol. 1, 2006, no. 4, 155-161 A Note on Certain Stability and Limiting Properties of ν-infinitely divisible distributions Tomasz J. Kozubowski 1 Department of Mathematics &
More informationThe Bayesian Choice. Christian P. Robert. From Decision-Theoretic Foundations to Computational Implementation. Second Edition.
Christian P. Robert The Bayesian Choice From Decision-Theoretic Foundations to Computational Implementation Second Edition With 23 Illustrations ^Springer" Contents Preface to the Second Edition Preface
More informationA Few Special Distributions and Their Properties
A Few Special Distributions and Their Properties Econ 690 Purdue University Justin L. Tobias (Purdue) Distributional Catalog 1 / 20 Special Distributions and Their Associated Properties 1 Uniform Distribution
More informationESTIMATOR IN BURR XII DISTRIBUTION
Journal of Reliability and Statistical Studies; ISSN (Print): 0974-804, (Online): 9-5666 Vol. 0, Issue (07): 7-6 ON THE VARIANCE OF P ( Y < X) ESTIMATOR IN BURR XII DISTRIBUTION M. Khorashadizadeh*, S.
More informationMonte Carlo Studies. The response in a Monte Carlo study is a random variable.
Monte Carlo Studies The response in a Monte Carlo study is a random variable. The response in a Monte Carlo study has a variance that comes from the variance of the stochastic elements in the data-generating
More information3 Joint Distributions 71
2.2.3 The Normal Distribution 54 2.2.4 The Beta Density 58 2.3 Functions of a Random Variable 58 2.4 Concluding Remarks 64 2.5 Problems 64 3 Joint Distributions 71 3.1 Introduction 71 3.2 Discrete Random
More informationTesting Goodness-of-Fit for Exponential Distribution Based on Cumulative Residual Entropy
This article was downloaded by: [Ferdowsi University] On: 16 April 212, At: 4:53 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 172954 Registered office: Mortimer
More informationModeling Hydrologic Chanae
Modeling Hydrologic Chanae Statistical Methods Richard H. McCuen Department of Civil and Environmental Engineering University of Maryland m LEWIS PUBLISHERS A CRC Press Company Boca Raton London New York
More informationINDEX DES TRADUCTIONS ANGLAISES
STATISTIQUE THÉORIQUE ET APPLIQUÉE Tome 1 Statistique descriptive et bases de l inférence statistique Pierre Dagnelie INDEX DES TRADUCTIONS ANGLAISES Bruxelles, De Boeck, 2013, 517 p. ISBN 978-2-8041-7560-3
More informationDistribution Fitting (Censored Data)
Distribution Fitting (Censored Data) Summary... 1 Data Input... 2 Analysis Summary... 3 Analysis Options... 4 Goodness-of-Fit Tests... 6 Frequency Histogram... 8 Comparison of Alternative Distributions...
More informationSCHEME OF EXAMINATION
APPENDIX AE28 MANONMANIAM SUNDARANAR UNIVERSITY, TIRUNELVELI 12. DIRECTORATE OF DISTANCE AND CONTINUING EDUCATION POSTGRADUATE DIPLOMA IN STATISTICAL METHODS AND APPLICATIONS (Effective from the Academic
More informationHANDBOOK OF APPLICABLE MATHEMATICS
HANDBOOK OF APPLICABLE MATHEMATICS Chief Editor: Walter Ledermann Volume II: Probability Emlyn Lloyd University oflancaster A Wiley-Interscience Publication JOHN WILEY & SONS Chichester - New York - Brisbane
More informationPoint and Interval Estimation for Gaussian Distribution, Based on Progressively Type-II Censored Samples
90 IEEE TRANSACTIONS ON RELIABILITY, VOL. 52, NO. 1, MARCH 2003 Point and Interval Estimation for Gaussian Distribution, Based on Progressively Type-II Censored Samples N. Balakrishnan, N. Kannan, C. T.
More informationContents. Part I: Fundamentals of Bayesian Inference 1
Contents Preface xiii Part I: Fundamentals of Bayesian Inference 1 1 Probability and inference 3 1.1 The three steps of Bayesian data analysis 3 1.2 General notation for statistical inference 4 1.3 Bayesian
More informationNumerical Analysis for Statisticians
Kenneth Lange Numerical Analysis for Statisticians Springer Contents Preface v 1 Recurrence Relations 1 1.1 Introduction 1 1.2 Binomial CoefRcients 1 1.3 Number of Partitions of a Set 2 1.4 Horner's Method
More informationAppendix F. Computational Statistics Toolbox. The Computational Statistics Toolbox can be downloaded from:
Appendix F Computational Statistics Toolbox The Computational Statistics Toolbox can be downloaded from: http://www.infinityassociates.com http://lib.stat.cmu.edu. Please review the readme file for installation
More informationInstitute of Actuaries of India
Institute of Actuaries of India Subject CT3 Probability and Mathematical Statistics For 2018 Examinations Subject CT3 Probability and Mathematical Statistics Core Technical Syllabus 1 June 2017 Aim The
More informationMohsen Pourahmadi. 1. A sampling theorem for multivariate stationary processes. J. of Multivariate Analysis, Vol. 13, No. 1 (1983),
Mohsen Pourahmadi PUBLICATIONS Books and Editorial Activities: 1. Foundations of Time Series Analysis and Prediction Theory, John Wiley, 2001. 2. Computing Science and Statistics, 31, 2000, the Proceedings
More informationOn Asymptotic Distribution of Sample Central. Moments in Normal-Uniform Distribution
International Mathematical Forum, Vol. 8, 2013, no. 8, 395-399 On Asymptotic Distribution of Sample Central Moments in Normal-Uniform Distribution Narges Abbasi Department of Statistics, Payame Noor University,
More informationContents. Acknowledgments. xix
Table of Preface Acknowledgments page xv xix 1 Introduction 1 The Role of the Computer in Data Analysis 1 Statistics: Descriptive and Inferential 2 Variables and Constants 3 The Measurement of Variables
More informationApplied Probability and Stochastic Processes
Applied Probability and Stochastic Processes In Engineering and Physical Sciences MICHEL K. OCHI University of Florida A Wiley-Interscience Publication JOHN WILEY & SONS New York - Chichester Brisbane
More informationLinear Classification
Linear Classification Lili MOU moull12@sei.pku.edu.cn http://sei.pku.edu.cn/ moull12 23 April 2015 Outline Introduction Discriminant Functions Probabilistic Generative Models Probabilistic Discriminative
More informationNonparametric Bayesian Methods (Gaussian Processes)
[70240413 Statistical Machine Learning, Spring, 2015] Nonparametric Bayesian Methods (Gaussian Processes) Jun Zhu dcszj@mail.tsinghua.edu.cn http://bigml.cs.tsinghua.edu.cn/~jun State Key Lab of Intelligent
More informationPattern Recognition and Machine Learning. Bishop Chapter 2: Probability Distributions
Pattern Recognition and Machine Learning Chapter 2: Probability Distributions Cécile Amblard Alex Kläser Jakob Verbeek October 11, 27 Probability Distributions: General Density Estimation: given a finite
More informationarxiv: v1 [stat.ap] 31 May 2016
Some estimators of the PMF and CDF of the arxiv:1605.09652v1 [stat.ap] 31 May 2016 Logarithmic Series Distribution Sudhansu S. Maiti, Indrani Mukherjee and Monojit Das Department of Statistics, Visva-Bharati
More informationPattern Recognition and Machine Learning
Christopher M. Bishop Pattern Recognition and Machine Learning ÖSpri inger Contents Preface Mathematical notation Contents vii xi xiii 1 Introduction 1 1.1 Example: Polynomial Curve Fitting 4 1.2 Probability
More informationIndex. 0 1 loss function, 467
Index 0 1 loss function, 467 a priori,374 abs command, 685 absolutely continuous jointly, 85 absolutely continuous random variable, 52 acceptance probability, 644 action space, 464 additive, 5 additive
More informationREFERENCES AND FURTHER STUDIES
REFERENCES AND FURTHER STUDIES by..0. on /0/. For personal use only.. Afifi, A. A., and Azen, S. P. (), Statistical Analysis A Computer Oriented Approach, Academic Press, New York.. Alvarez, A. R., Welter,
More informationDeep Variational Inference. FLARE Reading Group Presentation Wesley Tansey 9/28/2016
Deep Variational Inference FLARE Reading Group Presentation Wesley Tansey 9/28/2016 What is Variational Inference? What is Variational Inference? Want to estimate some distribution, p*(x) p*(x) What is
More informationPrerequisite: STATS 7 or STATS 8 or AP90 or (STATS 120A and STATS 120B and STATS 120C). AP90 with a minimum score of 3
University of California, Irvine 2017-2018 1 Statistics (STATS) Courses STATS 5. Seminar in Data Science. 1 Unit. An introduction to the field of Data Science; intended for entering freshman and transfers.
More informationMotivation Scale Mixutres of Normals Finite Gaussian Mixtures Skew-Normal Models. Mixture Models. Econ 690. Purdue University
Econ 690 Purdue University In virtually all of the previous lectures, our models have made use of normality assumptions. From a computational point of view, the reason for this assumption is clear: combined
More informationFundamentals of Applied Probability and Random Processes
Fundamentals of Applied Probability and Random Processes,nd 2 na Edition Oliver C. Ibe University of Massachusetts, LoweLL, Massachusetts ip^ W >!^ AMSTERDAM BOSTON HEIDELBERG LONDON NEW YORK OXFORD PARIS
More informationBayesian Regression Linear and Logistic Regression
When we want more than point estimates Bayesian Regression Linear and Logistic Regression Nicole Beckage Ordinary Least Squares Regression and Lasso Regression return only point estimates But what if we
More informationISSN: ISO 9001:2008 Certified International Journal of Engineering and Innovative Technology (IJEIT) Volume 4, Issue 6, December 2014
Bayesian Estimation for the Reliability Function of Pareto Type I Distribution under Generalized Square Error Loss Function Dr. Huda A. Rasheed, Najam A. Aleawy Al-Gazi Abstract The main objective of this
More informationLeast Absolute Value vs. Least Squares Estimation and Inference Procedures in Regression Models with Asymmetric Error Distributions
Journal of Modern Applied Statistical Methods Volume 8 Issue 1 Article 13 5-1-2009 Least Absolute Value vs. Least Squares Estimation and Inference Procedures in Regression Models with Asymmetric Error
More informationAN INTRODUCTION TO PROBABILITY AND STATISTICS
AN INTRODUCTION TO PROBABILITY AND STATISTICS WILEY SERIES IN PROBABILITY AND STATISTICS Established by WALTER A. SHEWHART and SAMUEL S. WILKS Editors: David J. Balding, Noel A. C. Cressie, Garrett M.
More informationEstimation in an Exponentiated Half Logistic Distribution under Progressively Type-II Censoring
Communications of the Korean Statistical Society 2011, Vol. 18, No. 5, 657 666 DOI: http://dx.doi.org/10.5351/ckss.2011.18.5.657 Estimation in an Exponentiated Half Logistic Distribution under Progressively
More informationDistributed Estimation, Information Loss and Exponential Families. Qiang Liu Department of Computer Science Dartmouth College
Distributed Estimation, Information Loss and Exponential Families Qiang Liu Department of Computer Science Dartmouth College Statistical Learning / Estimation Learning generative models from data Topic
More informationApplication of Parametric Homogeneity of Variances Tests under Violation of Classical Assumption
Application of Parametric Homogeneity of Variances Tests under Violation of Classical Assumption Alisa A. Gorbunova and Boris Yu. Lemeshko Novosibirsk State Technical University Department of Applied Mathematics,
More informationResearch Article The Laplace Likelihood Ratio Test for Heteroscedasticity
International Mathematics and Mathematical Sciences Volume 2011, Article ID 249564, 7 pages doi:10.1155/2011/249564 Research Article The Laplace Likelihood Ratio Test for Heteroscedasticity J. Martin van
More informationJournal of Biostatistics and Epidemiology
Journal of Biostatistics and Epidemiology Original Article Robust correlation coefficient goodness-of-fit test for the Gumbel distribution Abbas Mahdavi 1* 1 Department of Statistics, School of Mathematical
More informationINFORMATION THEORY AND STATISTICS
INFORMATION THEORY AND STATISTICS Solomon Kullback DOVER PUBLICATIONS, INC. Mineola, New York Contents 1 DEFINITION OF INFORMATION 1 Introduction 1 2 Definition 3 3 Divergence 6 4 Examples 7 5 Problems...''.
More informationMultilevel Statistical Models: 3 rd edition, 2003 Contents
Multilevel Statistical Models: 3 rd edition, 2003 Contents Preface Acknowledgements Notation Two and three level models. A general classification notation and diagram Glossary Chapter 1 An introduction
More information1. A remark to the law of the iterated logarithm. Studia Sci. Math. Hung. 7 (1972)
1 PUBLICATION LIST OF ISTVÁN BERKES 1. A remark to the law of the iterated logarithm. Studia Sci. Math. Hung. 7 (1972) 189-197. 2. Functional limit theorems for lacunary trigonometric and Walsh series.
More informationEstimation for generalized half logistic distribution based on records
Journal of the Korean Data & Information Science Society 202, 236, 249 257 http://dx.doi.org/0.7465/jkdi.202.23.6.249 한국데이터정보과학회지 Estimation for generalized half logistic distribution based on records
More informationAPPLICATION AND POWER OF PARAMETRIC CRITERIA FOR TESTING THE HOMOGENEITY OF VARIANCES. PART IV
DOI 10.1007/s11018-017-1213-4 Measurement Techniques, Vol. 60, No. 5, August, 2017 APPLICATION AND POWER OF PARAMETRIC CRITERIA FOR TESTING THE HOMOGENEITY OF VARIANCES. PART IV B. Yu. Lemeshko and T.
More informationBayesian Models in Machine Learning
Bayesian Models in Machine Learning Lukáš Burget Escuela de Ciencias Informáticas 2017 Buenos Aires, July 24-29 2017 Frequentist vs. Bayesian Frequentist point of view: Probability is the frequency of
More informationASSESSING A VECTOR PARAMETER
SUMMARY ASSESSING A VECTOR PARAMETER By D.A.S. Fraser and N. Reid Department of Statistics, University of Toronto St. George Street, Toronto, Canada M5S 3G3 dfraser@utstat.toronto.edu Some key words. Ancillary;
More informationLog Gaussian Cox Processes. Chi Group Meeting February 23, 2016
Log Gaussian Cox Processes Chi Group Meeting February 23, 2016 Outline Typical motivating application Introduction to LGCP model Brief overview of inference Applications in my work just getting started
More informationOn Bayesian Inference with Conjugate Priors for Scale Mixtures of Normal Distributions
Journal of Applied Probability & Statistics Vol. 5, No. 1, xxx xxx c 2010 Dixie W Publishing Corporation, U. S. A. On Bayesian Inference with Conjugate Priors for Scale Mixtures of Normal Distributions
More informationParametric Inference Maximum Likelihood Inference Exponential Families Expectation Maximization (EM) Bayesian Inference Statistical Decison Theory
Statistical Inference Parametric Inference Maximum Likelihood Inference Exponential Families Expectation Maximization (EM) Bayesian Inference Statistical Decison Theory IP, José Bioucas Dias, IST, 2007
More informationNONPARAMETRICS. Statistical Methods Based on Ranks E. L. LEHMANN HOLDEN-DAY, INC. McGRAW-HILL INTERNATIONAL BOOK COMPANY
NONPARAMETRICS Statistical Methods Based on Ranks E. L. LEHMANN University of California, Berkeley With the special assistance of H. J. M. D'ABRERA University of California, Berkeley HOLDEN-DAY, INC. San
More informationApplication of Variance Homogeneity Tests Under Violation of Normality Assumption
Application of Variance Homogeneity Tests Under Violation of Normality Assumption Alisa A. Gorbunova, Boris Yu. Lemeshko Novosibirsk State Technical University Novosibirsk, Russia e-mail: gorbunova.alisa@gmail.com
More informationKarunarathna B. Kulasekera
RESUME Karunarathna B. Kulasekera PERSONAL DATA Professor Department of Mathematical Sciences Clemson University Clemson, SC 29634-1907 Telephone: 864-656-5231 Fax: 864-656-5230 e-mail: kk@ces.clemson.edu
More informationDeccan Education Society s FERGUSSON COLLEGE, PUNE (AUTONOMOUS) SYLLABUS UNDER AUTONOMY. FIRST YEAR B.Sc.(Computer Science) SEMESTER I
Deccan Education Society s FERGUSSON COLLEGE, PUNE (AUTONOMOUS) SYLLABUS UNDER AUTONOMY FIRST YEAR B.Sc.(Computer Science) SEMESTER I SYLLABUS FOR F.Y.B.Sc.(Computer Science) STATISTICS Academic Year 2016-2017
More informationPRINCIPLES OF STATISTICAL INFERENCE
Advanced Series on Statistical Science & Applied Probability PRINCIPLES OF STATISTICAL INFERENCE from a Neo-Fisherian Perspective Luigi Pace Department of Statistics University ofudine, Italy Alessandra
More informationCURRICULUM VITAE. Yoshihiko KONNO. August 31, Personal. Japan Women s University, Mejirodai, Bunkyo-ku, Tokyo , Japan
CURRICULUM VITAE Yoshihiko KONNO August 31, 2017 Personal Date/Place of Birth Citizenship Mailing address Email address Weg-page September 9, 1961, Japan Japan Japan Women s University, 2-8-1 Mejirodai,
More informationStatistícal Methods for Spatial Data Analysis
Texts in Statistícal Science Statistícal Methods for Spatial Data Analysis V- Oliver Schabenberger Carol A. Gotway PCT CHAPMAN & K Contents Preface xv 1 Introduction 1 1.1 The Need for Spatial Analysis
More informationCAM Ph.D. Qualifying Exam in Numerical Analysis CONTENTS
CAM Ph.D. Qualifying Exam in Numerical Analysis CONTENTS Preliminaries Round-off errors and computer arithmetic, algorithms and convergence Solutions of Equations in One Variable Bisection method, fixed-point
More informationRonald Christensen. University of New Mexico. Albuquerque, New Mexico. Wesley Johnson. University of California, Irvine. Irvine, California
Texts in Statistical Science Bayesian Ideas and Data Analysis An Introduction for Scientists and Statisticians Ronald Christensen University of New Mexico Albuquerque, New Mexico Wesley Johnson University
More informationACTEX CAS EXAM 3 STUDY GUIDE FOR MATHEMATICAL STATISTICS
ACTEX CAS EXAM 3 STUDY GUIDE FOR MATHEMATICAL STATISTICS TABLE OF CONTENTS INTRODUCTORY NOTE NOTES AND PROBLEM SETS Section 1 - Point Estimation 1 Problem Set 1 15 Section 2 - Confidence Intervals and
More informationBayesian Model Diagnostics and Checking
Earvin Balderama Quantitative Ecology Lab Department of Forestry and Environmental Resources North Carolina State University April 12, 2013 1 / 34 Introduction MCMCMC 2 / 34 Introduction MCMCMC Steps in
More information1 Uniform Distribution. 2 Gamma Distribution. 3 Inverse Gamma Distribution. 4 Multivariate Normal Distribution. 5 Multivariate Student-t Distribution
A Few Special Distributions Their Properties Econ 675 Iowa State University November 1 006 Justin L Tobias (ISU Distributional Catalog November 1 006 1 / 0 Special Distributions Their Associated Properties
More informationINVERTED KUMARASWAMY DISTRIBUTION: PROPERTIES AND ESTIMATION
Pak. J. Statist. 2017 Vol. 33(1), 37-61 INVERTED KUMARASWAMY DISTRIBUTION: PROPERTIES AND ESTIMATION A. M. Abd AL-Fattah, A.A. EL-Helbawy G.R. AL-Dayian Statistics Department, Faculty of Commerce, AL-Azhar
More informationSTATISTICS SYLLABUS UNIT I
STATISTICS SYLLABUS UNIT I (Probability Theory) Definition Classical and axiomatic approaches.laws of total and compound probability, conditional probability, Bayes Theorem. Random variable and its distribution
More informationIDL Advanced Math & Stats Module
IDL Advanced Math & Stats Module Regression List of Routines and Functions Multiple Linear Regression IMSL_REGRESSORS IMSL_MULTIREGRESS IMSL_MULTIPREDICT Generates regressors for a general linear model.
More informationExact Linear Likelihood Inference for Laplace
Exact Linear Likelihood Inference for Laplace Prof. N. Balakrishnan McMaster University, Hamilton, Canada bala@mcmaster.ca p. 1/52 Pierre-Simon Laplace 1749 1827 p. 2/52 Laplace s Biography Born: On March
More informationOn Introducing Asymmetry into Circular Distributions
Statistics in the Twenty-First Century: Secial Volume In Honour of Distinguished Professor Dr. Mir Masoom Ali On the Occasion of his 75th Birthday Anniversary PJSOR, Vol. 8, No. 3, ages 531-535, July 2012
More informationSTA 4273H: Statistical Machine Learning
STA 4273H: Statistical Machine Learning Russ Salakhutdinov Department of Statistics! rsalakhu@utstat.toronto.edu! http://www.utstat.utoronto.ca/~rsalakhu/ Sidney Smith Hall, Room 6002 Lecture 3 Linear
More informationExam details. Final Review Session. Things to Review
Exam details Final Review Session Short answer, similar to book problems Formulae and tables will be given You CAN use a calculator Date and Time: Dec. 7, 006, 1-1:30 pm Location: Osborne Centre, Unit
More informationLIST OF PUBLICATIONS. 1. J.-P. Kreiss and E. Paparoditis, Bootstrap for Time Series: Theory and Applications, Springer-Verlag, New York, To appear.
LIST OF PUBLICATIONS BOOKS 1. J.-P. Kreiss and E. Paparoditis, Bootstrap for Time Series: Theory and Applications, Springer-Verlag, New York, To appear. JOURNAL PAPERS 61. D. Pilavakis, E. Paparoditis
More informationI I FINAL, 01 Jun 8.4 to 31 May TITLE AND SUBTITLE 5 * _- N, '. ', -;
R AD-A237 850 E........ I N 11111IIIII U 1 1I!til II II... 1. AGENCY USE ONLY Leave 'VanK) I2. REPORT DATE 3 REPORT TYPE AND " - - I I FINAL, 01 Jun 8.4 to 31 May 88 4. TITLE AND SUBTITLE 5 * _- N, '.
More informationTheory and Methods of Statistical Inference
PhD School in Statistics cycle XXIX, 2014 Theory and Methods of Statistical Inference Instructors: B. Liseo, L. Pace, A. Salvan (course coordinator), N. Sartori, A. Tancredi, L. Ventura Syllabus Some prerequisites:
More information