5.5.3 Statistical Innovative Trend Test Application Crossing Trend Analysis Methodology Rational Concept...
|
|
|
- Silas Mervyn Carson
- 6 years ago
- Views:
Transcription
1 Contents 1 Introduction General Trend Definition and Analysis Conceptual and Visual Trends Mathematical Trend Statistical Trend Trend in Some Disciplines Atmospheric Sciences Environmental Sciences Earth Sciences Engineering Global Warming Climate Change Social Sciences Pros and Cons of Trend Analysis Future Research Directions Purpose of This Book References Uncertainty and Time Series General Random and Randomness Empirical Frequency and Distribution Function Empirical Frequency and Trend Theoretical Probability Distribution Function (Pdf) Statistical Modeling Deterministic-Uncertain Model Probabilistic-Statistical Model Transitional Probability Model Stochastic Models Homogeneity (Consistency) Stationarity Periodicity (Seasonality) ix
2 x Contents 2.7 Time Series Truncation Statistical Truncations Data Smoothing Moving Averages Difference Smoothing Jump (Shift) Correlation Coefficients Pearson Correlation Coefficient Kendall Correlation Coefficient Spearman Correlation Coefficient Persistence/Nonrandomness Short-Memory (Correlation) Components Long-Memory (Persistence) Component References Statistical Trend Tests General Nonparametric Tests Data Ordering (Ranks) Statistical Tests Wald Wolfowitz Sign Test Sign Difference Test Run Test Mann Whitney (MW) Test Kruskal Wallis (KW) Test Nonparametric Correlation Coefficient Spearman s Rho Test of Trend Turning Point Test Mann Kendall (MK) Test Two-Sample Wilcoxon Test von Neuman Test Cumulative Departures Test Bayesian Test Relative Error Test t Test Cramer Test F Test Truncation Test Deviations Test Subtraction Test Şen Autorun Test Seasonal Kendall Test
3 Contents xi 3.4 Unit Root Model Trend Determination Integration and Dickey Fuller (DF) Test The Kwiatkowski, Phillips, Schmidt, and Shin Test Critical Values of the KPSS Test Empirical Power of the KPSS Example: Comparison of the DF and KPSS Tests for Several Macro-Economic Time Series Parametric Tests Regression Analysis Regression Line Assumptions Goodness of Fit (R 2 ) for Regression Cumulative Sum (CUSUM) Method References Temporal Trend Analysis General Visual Inspection Monotonic Trend Analysis Scatter Diagrams and Regression Model Linear Regression Model Statistical Procedure Unrestricted Regression Model Application Partial Regression Method (PRM) Cluster Regression and Markov Chain Cluster Regression Model Application and Discussion Trend Over-whitening Procedures Over-whitening (OW) Process Simulation Application References Innovative Trend Analyses General Probability Distribution-Statistical Parameter Trend Implications Innovative Trend Identification Methodologies Application Innovative Trend Simulation Fundamental Methodology Innovative Trend Significance Test Deterministic Basis Stochastic Basis
4 xii Contents Statistical Innovative Trend Test Application Crossing Trend Analysis Methodology Rational Concept Theoretical Background Monte Carlo Simulations Application References Spatial Trend Analysis General Numerical Solution Spatial Data Analysis Homogeneity and Isotropy Spatial Trend Surfaces Horizontal Plane Horizontal Planes Inclined Trend Plane Inclined Trend Planes Curved Trend Surface Random Surface Spatial Dependence Function (SDF) Spatial Correlation Parameter Calculation Double Mass Curve Test Trend Surface Analysis Planer Trend Regression Analysis Polynomial Trend Regression Analysis Kriging Methodology Triple Diagram Model (TDM) Parallel-Triple Model Serial-Triple Model References Trend Variability Detection General Variability Measures Range Standard Deviation The Interquartile Range (IQR) Investment Variability Trend and Variability Detection by Innovative Methodology Methodology Simulation Study Applications Trend Significance Limits
5 Contents xiii 7.5 Trend and Variability Analyses by Innovative and Classical Methodologies Şen Innovative Trend Analysis Application and Interpretations Probability Distribution Functions (pdf) Different Trends Trend and Variability Innovative Trend Template and Significance Limits References Partial Trend Detection General Qualitative Partial Trend Methodology Previous Works Innovative Piecewise Trend Analysis Innovative Trend Template Stochastic Simulation Approach ]8.7 Data and the Study Area Partial Trend Groups Partial Trend Lines References Index
6
Modeling 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
Introduction and Descriptive Statistics p. 1 Introduction to Statistics p. 3 Statistics, Science, and Observations p. 5 Populations and Samples p.
Preface p. xi Introduction and Descriptive Statistics p. 1 Introduction to Statistics p. 3 Statistics, Science, and Observations p. 5 Populations and Samples p. 6 The Scientific Method and the Design of
Rank-Based Methods. Lukas Meier
Rank-Based Methods Lukas Meier 20.01.2014 Introduction Up to now we basically always used a parametric family, like the normal distribution N (µ, σ 2 ) for modeling random data. Based on observed data
Textbook Examples of. SPSS Procedure
Textbook s of IBM SPSS Procedures Each SPSS procedure listed below has its own section in the textbook. These sections include a purpose statement that describes the statistical test, identification of
Transition Passage to Descriptive Statistics 28
viii Preface xiv chapter 1 Introduction 1 Disciplines That Use Quantitative Data 5 What Do You Mean, Statistics? 6 Statistics: A Dynamic Discipline 8 Some Terminology 9 Problems and Answers 12 Scales of
DETAILED CONTENTS PART I INTRODUCTION AND DESCRIPTIVE STATISTICS. 1. Introduction to Statistics
DETAILED CONTENTS About the Author Preface to the Instructor To the Student How to Use SPSS With This Book PART I INTRODUCTION AND DESCRIPTIVE STATISTICS 1. Introduction to Statistics 1.1 Descriptive and
Nonparametric Statistics
Nonparametric Statistics Nonparametric or Distribution-free statistics: used when data are ordinal (i.e., rankings) used when ratio/interval data are not normally distributed (data are converted to ranks)
Contents. 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
Lecture 5: Unit Roots, Cointegration and Error Correction Models The Spurious Regression Problem
Lecture 5: Unit Roots, Cointegration and Error Correction Models The Spurious Regression Problem Prof. Massimo Guidolin 20192 Financial Econometrics Winter/Spring 2018 Overview Stochastic vs. deterministic
Testing for non-stationarity
20 November, 2009 Overview The tests for investigating the non-stationary of a time series falls into four types: 1 Check the null that there is a unit root against stationarity. Within these, there are
BCT Lecture 3. Lukas Vacha.
BCT Lecture 3 Lukas Vacha vachal@utia.cas.cz Stationarity and Unit Root Testing Why do we need to test for Non-Stationarity? The stationarity or otherwise of a series can strongly influence its behaviour
Types of Statistical Tests DR. MIKE MARRAPODI
Types of Statistical Tests DR. MIKE MARRAPODI Tests t tests ANOVA Correlation Regression Multivariate Techniques Non-parametric t tests One sample t test Independent t test Paired sample t test One sample
3 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
Chapter 15: Nonparametric Statistics Section 15.1: An Overview of Nonparametric Statistics
Section 15.1: An Overview of Nonparametric Statistics Understand Difference between Parametric and Nonparametric Statistical Procedures Parametric statistical procedures inferential procedures that rely
Nemours Biomedical Research Statistics Course. Li Xie Nemours Biostatistics Core October 14, 2014
Nemours Biomedical Research Statistics Course Li Xie Nemours Biostatistics Core October 14, 2014 Outline Recap Introduction to Logistic Regression Recap Descriptive statistics Variable type Example of
Graphical Techniques Stem and Leaf Box plot Histograms Cumulative Frequency Distributions
Class #8 Wednesday 9 February 2011 What did we cover last time? Description & Inference Robustness & Resistance Median & Quartiles Location, Spread and Symmetry (parallels from classical statistics: Mean,
Glossary. The ISI glossary of statistical terms provides definitions in a number of different languages:
Glossary The ISI glossary of statistical terms provides definitions in a number of different languages: http://isi.cbs.nl/glossary/index.htm Adjusted r 2 Adjusted R squared measures the proportion of the
STATISTICS ( CODE NO. 08 ) PAPER I PART - I
STATISTICS ( CODE NO. 08 ) PAPER I PART - I 1. Descriptive Statistics Types of data - Concepts of a Statistical population and sample from a population ; qualitative and quantitative data ; nominal and
Introduction to Eco n o m et rics
2008 AGI-Information Management Consultants May be used for personal purporses only or by libraries associated to dandelon.com network. Introduction to Eco n o m et rics Third Edition G.S. Maddala Formerly
Univariate, Nonstationary Processes
Univariate, Nonstationary Processes Jamie Monogan University of Georgia March 20, 2018 Jamie Monogan (UGA) Univariate, Nonstationary Processes March 20, 2018 1 / 14 Objectives By the end of this meeting,
CHI SQUARE ANALYSIS 8/18/2011 HYPOTHESIS TESTS SO FAR PARAMETRIC VS. NON-PARAMETRIC
CHI SQUARE ANALYSIS I N T R O D U C T I O N T O N O N - P A R A M E T R I C A N A L Y S E S HYPOTHESIS TESTS SO FAR We ve discussed One-sample t-test Dependent Sample t-tests Independent Samples t-tests
Nonparametric Statistics Notes
Nonparametric Statistics Notes Chapter 5: Some Methods Based on Ranks Jesse Crawford Department of Mathematics Tarleton State University (Tarleton State University) Ch 5: Some Methods Based on Ranks 1
G. S. Maddala Kajal Lahiri. WILEY A John Wiley and Sons, Ltd., Publication
G. S. Maddala Kajal Lahiri WILEY A John Wiley and Sons, Ltd., Publication TEMT Foreword Preface to the Fourth Edition xvii xix Part I Introduction and the Linear Regression Model 1 CHAPTER 1 What is Econometrics?
Non-parametric Tests for Complete Data
Non-parametric Tests for Complete Data Non-parametric Tests for Complete Data Vilijandas Bagdonavičius Julius Kruopis Mikhail S. Nikulin First published 2011 in Great Britain and the United States by
PSY 307 Statistics for the Behavioral Sciences. Chapter 20 Tests for Ranked Data, Choosing Statistical Tests
PSY 307 Statistics for the Behavioral Sciences Chapter 20 Tests for Ranked Data, Choosing Statistical Tests What To Do with Non-normal Distributions Tranformations (pg 382): The shape of the distribution
Nonstationary Time Series:
Nonstationary Time Series: Unit Roots Egon Zakrajšek Division of Monetary Affairs Federal Reserve Board Summer School in Financial Mathematics Faculty of Mathematics & Physics University of Ljubljana September
On Consistency of Tests for Stationarity in Autoregressive and Moving Average Models of Different Orders
American Journal of Theoretical and Applied Statistics 2016; 5(3): 146-153 http://www.sciencepublishinggroup.com/j/ajtas doi: 10.11648/j.ajtas.20160503.20 ISSN: 2326-8999 (Print); ISSN: 2326-9006 (Online)
Statistícal 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
Statistics and Measurement Concepts with OpenStat
Statistics and Measurement Concepts with OpenStat William Miller Statistics and Measurement Concepts with OpenStat William Miller Urbandale, Iowa USA ISBN 978-1-4614-5742-8 ISBN 978-1-4614-5743-5 (ebook)
A Reference Guide for Statistical Tests Useful in Finance (Preliminary)
A Reference Guide for Statistical Tests Useful in Finance (Preliminary) Market Pattern Research, Inc. modified from the book The Strategic Analysis of Financial Markets Volume 1: Framework Steven D. Moffitt,
N Utilization of Nursing Research in Advanced Practice, Summer 2008
University of Michigan Deep Blue deepblue.lib.umich.edu 2008-07 536 - Utilization of ursing Research in Advanced Practice, Summer 2008 Tzeng, Huey-Ming Tzeng, H. (2008, ctober 1). Utilization of ursing
Response surface models for the Elliott, Rothenberg, Stock DF-GLS unit-root test
Response surface models for the Elliott, Rothenberg, Stock DF-GLS unit-root test Christopher F Baum Jesús Otero UK Stata Users Group Meetings, London, September 2017 Baum, Otero (BC, U. del Rosario) DF-GLS
Chapter 5 Identifying hydrological persistence
103 Chapter 5 Identifying hydrological persistence The previous chapter demonstrated that hydrologic data from across Australia is modulated by fluctuations in global climate modes. Various climate indices
Modelling Under Risk and Uncertainty
Modelling Under Risk and Uncertainty An Introduction to Statistical, Phenomenological and Computational Methods Etienne de Rocquigny Ecole Centrale Paris, Universite Paris-Saclay, France WILEY A John Wiley
Non-parametric tests, part A:
Two types of statistical test: Non-parametric tests, part A: Parametric tests: Based on assumption that the data have certain characteristics or "parameters": Results are only valid if (a) the data are
Darmstadt Discussion Papers in Economics
Darmstadt Discussion Papers in Economics The Effect of Linear Time Trends on Cointegration Testing in Single Equations Uwe Hassler Nr. 111 Arbeitspapiere des Instituts für Volkswirtschaftslehre Technische
COPYRIGHTED 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
Time Series Analysis. James D. Hamilton PRINCETON UNIVERSITY PRESS PRINCETON, NEW JERSEY
Time Series Analysis James D. Hamilton PRINCETON UNIVERSITY PRESS PRINCETON, NEW JERSEY PREFACE xiii 1 Difference Equations 1.1. First-Order Difference Equations 1 1.2. pth-order Difference Equations 7
APPLIED TIME SERIES ECONOMETRICS
APPLIED TIME SERIES ECONOMETRICS Edited by HELMUT LÜTKEPOHL European University Institute, Florence MARKUS KRÄTZIG Humboldt University, Berlin CAMBRIDGE UNIVERSITY PRESS Contents Preface Notation and Abbreviations
11/18/2008. So run regression in first differences to examine association. 18 November November November 2008
Time Series Econometrics 7 Vijayamohanan Pillai N Unit Root Tests Vijayamohan: CDS M Phil: Time Series 7 1 Vijayamohan: CDS M Phil: Time Series 7 2 R 2 > DW Spurious/Nonsense Regression. Integrated but
Parametric versus Nonparametric Statistics-when to use them and which is more powerful? Dr Mahmoud Alhussami
Parametric versus Nonparametric Statistics-when to use them and which is more powerful? Dr Mahmoud Alhussami Parametric Assumptions The observations must be independent. Dependent variable should be continuous
On detection of unit roots generalizing the classic Dickey-Fuller approach
On detection of unit roots generalizing the classic Dickey-Fuller approach A. Steland Ruhr-Universität Bochum Fakultät für Mathematik Building NA 3/71 D-4478 Bochum, Germany February 18, 25 1 Abstract
SPSS Guide For MMI 409
SPSS Guide For MMI 409 by John Wong March 2012 Preface Hopefully, this document can provide some guidance to MMI 409 students on how to use SPSS to solve many of the problems covered in the D Agostino
Time Series Analysis. James D. Hamilton PRINCETON UNIVERSITY PRESS PRINCETON, NEW JERSEY
Time Series Analysis James D. Hamilton PRINCETON UNIVERSITY PRESS PRINCETON, NEW JERSEY & Contents PREFACE xiii 1 1.1. 1.2. Difference Equations First-Order Difference Equations 1 /?th-order Difference
Kernel-based Approximation. Methods using MATLAB. Gregory Fasshauer. Interdisciplinary Mathematical Sciences. Michael McCourt.
SINGAPORE SHANGHAI Vol TAIPEI - Interdisciplinary Mathematical Sciences 19 Kernel-based Approximation Methods using MATLAB Gregory Fasshauer Illinois Institute of Technology, USA Michael McCourt University
CHAPTER 17 CHI-SQUARE AND OTHER NONPARAMETRIC TESTS FROM: PAGANO, R. R. (2007)
FROM: PAGANO, R. R. (007) I. INTRODUCTION: DISTINCTION BETWEEN PARAMETRIC AND NON-PARAMETRIC TESTS Statistical inference tests are often classified as to whether they are parametric or nonparametric Parameter
Response surface models for the Elliott, Rothenberg, Stock DF-GLS unit-root test
Response surface models for the Elliott, Rothenberg, Stock DF-GLS unit-root test Christopher F Baum Jesús Otero Stata Conference, Baltimore, July 2017 Baum, Otero (BC, U. del Rosario) DF-GLS response surfaces
A nonparametric test for seasonal unit roots
Robert M. Kunst robert.kunst@univie.ac.at University of Vienna and Institute for Advanced Studies Vienna To be presented in Innsbruck November 7, 2007 Abstract We consider a nonparametric test for the
What is (certain) Spatio-Temporal Data?
What is (certain) Spatio-Temporal Data? A spatio-temporal database stores triples (oid, time, loc) In the best case, this allows to look up the location of an object at any time 2 What is (certain) Spatio-Temporal
Rank tests for short memory stationarity
Rank tests for short memory stationarity Pranab K. Sen jointly with Matteo M. Pelagatti University of North Carolina at Chapel Hill Università degli Studi di Milano-Bicocca 50th Anniversary of the Department
We are IntechOpen, the world s leading publisher of Open Access books Built by scientists, for scientists. International authors and editors
We are IntechOpen, the world s leading publisher of Open Access books Built by scientists, for scientists 3,900 6,000 20M Open access books available International authors and editors Downloads Our authors
Statistical Hypothesis Testing with SAS and R
Statistical Hypothesis Testing with SAS and R Statistical Hypothesis Testing with SAS and R Dirk Taeger Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute
TABLE 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
HYPOTHESIS TESTING II TESTS ON MEANS. Sorana D. Bolboacă
HYPOTHESIS TESTING II TESTS ON MEANS Sorana D. Bolboacă OBJECTIVES Significance value vs p value Parametric vs non parametric tests Tests on means: 1 Dec 14 2 SIGNIFICANCE LEVEL VS. p VALUE Materials and
PART 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
ECONOMICS 7200 MODERN TIME SERIES ANALYSIS Econometric Theory and Applications
ECONOMICS 7200 MODERN TIME SERIES ANALYSIS Econometric Theory and Applications Yongmiao Hong Department of Economics & Department of Statistical Sciences Cornell University Spring 2019 Time and uncertainty
4. Dresdner Probabilistik-Workshop. Probabilistic Tutorial. From the measured part to the probabilistic analysis. Part I
4. Dresdner Probabilistik-Workshop Probabilistic Tutorial From the measured part to the probabilistic analysis Part I Matthias Voigt (TU Dresden) Outline Part I 1. Introduction 2. Basic Statistics 3. Probabilistic
Hakone Seminar Recent Developments in Statistics
Hakone Seminar Recent Developments in Statistics November 12-14, 2015 Hotel Green Plaza Hakone: http://www.hgp.co.jp/language/english/sp/ Organizer: Masanobu TANIGUCHI (Research Institute for Science &
Bayesian Methods for Machine Learning
Bayesian Methods for Machine Learning CS 584: Big Data Analytics Material adapted from Radford Neal s tutorial (http://ftp.cs.utoronto.ca/pub/radford/bayes-tut.pdf), Zoubin Ghahramni (http://hunch.net/~coms-4771/zoubin_ghahramani_bayesian_learning.pdf),
Package TimeSeries.OBeu
Type Package Package TimeSeries.OBeu Title Time Series Analysis 'OpenBudgets' Version 1.2.2 Date 2018-01-20 January 22, 2018 Estimate and return the needed parameters for visualisations designed for 'OpenBudgets'
Nonparametric statistic methods. Waraphon Phimpraphai DVM, PhD Department of Veterinary Public Health
Nonparametric statistic methods Waraphon Phimpraphai DVM, PhD Department of Veterinary Public Health Measurement What are the 4 levels of measurement discussed? 1. Nominal or Classificatory Scale Gender,
Course Description - Master in of Mathematics Comprehensive exam& Thesis Tracks
Course Description - Master in of Mathematics Comprehensive exam& Thesis Tracks 1309701 Theory of ordinary differential equations Review of ODEs, existence and uniqueness of solutions for ODEs, existence
NON-PARAMETRIC STATISTICS * (http://www.statsoft.com)
NON-PARAMETRIC STATISTICS * (http://www.statsoft.com) 1. GENERAL PURPOSE 1.1 Brief review of the idea of significance testing To understand the idea of non-parametric statistics (the term non-parametric
Measuring the Cyclical Component of a Time Series: Proposal of a New Methodology *
Measuring the Cyclical Component of a Time Series: Proposal of a New Methodology * Maria Helena Ambrosio Dias ** Joilson Dias *** Abstract The objective of this paper is to present a simple technique to
Unit 14: Nonparametric Statistical Methods
Unit 14: Nonparametric Statistical Methods Statistics 571: Statistical Methods Ramón V. León 8/8/2003 Unit 14 - Stat 571 - Ramón V. León 1 Introductory Remarks Most methods studied so far have been based
What Are Nonparametric Statistics and When Do You Use Them? Jennifer Catrambone
What Are Nonparametric Statistics and When Do You Use Them? Jennifer Catrambone First, a bit about Parametric Statistics Data are expected to be randomly drawn from a normal population Minimum sample size
Cointegration and the joint con rmation hypothesis
Cointegration and the joint con rmation hypothesis VASCO J. GABRIEL Department of Economics, Birkbeck College, UK University of Minho, Portugal October 2001 Abstract Recent papers by Charemza and Syczewska
IGD-TP Exchange Forum n 5 WG1 Safety Case: Handling of uncertainties October th 2014, Kalmar, Sweden
IGD-TP Exchange Forum n 5 WG1 Safety Case: Handling of uncertainties October 28-30 th 2014, Kalmar, Sweden Comparison of probabilistic and alternative evidence theoretical methods for the handling of parameter
Bootstrapping Long Memory Tests: Some Monte Carlo Results
Bootstrapping Long Memory Tests: Some Monte Carlo Results Anthony Murphy and Marwan Izzeldin University College Dublin and Cass Business School. July 2004 - Preliminary Abstract We investigate the bootstrapped
Unit root problem, solution of difference equations Simple deterministic model, question of unit root
Unit root problem, solution of difference equations Simple deterministic model, question of unit root (1 φ 1 L)X t = µ, Solution X t φ 1 X t 1 = µ X t = A + Bz t with unknown z and unknown A (clearly X
My data doesn t look like that..
Testing assumptions My data doesn t look like that.. We have made a big deal about testing model assumptions each week. Bill Pine Testing assumptions Testing assumptions We have made a big deal about testing
Contents. 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
Yuri S. Popkov. Mathematical. Demoeconomy. Integrating Demographic and Economic Approaches DE GRUYTER
Yuri S. Popkov Mathematical Demoeconomy Integrating Demographic and Economic Approaches DE GRUYTER Contents Preface Part I v General principles of demoeconomics 1 The population-economy system 3 1.1 General
Statistical Inference Theory Lesson 46 Non-parametric Statistics
46.1-The Sign Test Statistical Inference Theory Lesson 46 Non-parametric Statistics 46.1 - Problem 1: (a). Let p equal the proportion of supermarkets that charge less than $2.15 a pound. H o : p 0.50 H
Nonparametric Statistics. Leah Wright, Tyler Ross, Taylor Brown
Nonparametric Statistics Leah Wright, Tyler Ross, Taylor Brown Before we get to nonparametric statistics, what are parametric statistics? These statistics estimate and test population means, while holding
Master of Science in Statistics A Proposal
1 Master of Science in Statistics A Proposal Rationale of the Program In order to cope up with the emerging complexity on the solutions of realistic problems involving several phenomena of nature it is
Forecasting using R. Rob J Hyndman. 2.3 Stationarity and differencing. Forecasting using R 1
Forecasting using R Rob J Hyndman 2.3 Stationarity and differencing Forecasting using R 1 Outline 1 Stationarity 2 Differencing 3 Unit root tests 4 Lab session 10 5 Backshift notation Forecasting using
Descriptive Statistics
Descriptive Statistics DS GA 1002 Probability and Statistics for Data Science http://www.cims.nyu.edu/~cfgranda/pages/dsga1002_fall17 Carlos Fernandez-Granda Descriptive statistics Techniques to visualize
Consider the trend-cycle decomposition of a time series y t
1 Unit Root Tests Consider the trend-cycle decomposition of a time series y t y t = TD t + TS t + C t = TD t + Z t The basic issue in unit root testing is to determine if TS t = 0. Two classes of tests,
The Seasonal KPSS Test When Neglecting Seasonal Dummies: A Monte Carlo analysis. Ghassen El Montasser, Talel Boufateh, Fakhri Issaoui
EERI Economics and Econometrics Research Institute The Seasonal KPSS Test When Neglecting Seasonal Dummies: A Monte Carlo analysis Ghassen El Montasser, Talel Boufateh, Fakhri Issaoui EERI Research Paper
Contents. Part I Statistical Background and Basic Data Handling 5. List of Figures List of Tables xix
Contents List of Figures List of Tables xix Preface Acknowledgements 1 Introduction 1 What is econometrics? 2 The stages of applied econometric work 2 Part I Statistical Background and Basic Data Handling
388 Index Differencing test ,232 Distributed lags , 147 arithmetic lag.
INDEX Aggregation... 104 Almon lag... 135-140,149 AR(1) process... 114-130,240,246,324-325,366,370,374 ARCH... 376-379 ARlMA... 365 Asymptotically unbiased... 13,50 Autocorrelation... 113-130, 142-150,324-325,365-369
Testing 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
ARDL Cointegration Tests for Beginner
ARDL Cointegration Tests for Beginner Tuck Cheong TANG Department of Economics, Faculty of Economics & Administration University of Malaya Email: tangtuckcheong@um.edu.my DURATION: 3 HOURS On completing
BEST ESTIMATE PLUS UNCERTAINTY SAFETY STUDIES AT THE CONCEPTUAL DESIGN PHASE OF THE ASTRID DEMONSTRATOR
BEST ESTIMATE PLUS UNCERTAINTY SAFETY STUDIES AT THE CONCEPTUAL DESIGN PHASE OF THE ASTRID DEMONSTRATOR M. Marquès CEA, DEN, DER F-13108, Saint-Paul-lez-Durance, France Advanced simulation in support to
TIME SERIES ANALYSIS. Forecasting and Control. Wiley. Fifth Edition GWILYM M. JENKINS GEORGE E. P. BOX GREGORY C. REINSEL GRETA M.
TIME SERIES ANALYSIS Forecasting and Control Fifth Edition GEORGE E. P. BOX GWILYM M. JENKINS GREGORY C. REINSEL GRETA M. LJUNG Wiley CONTENTS PREFACE TO THE FIFTH EDITION PREFACE TO THE FOURTH EDITION
EC821: Time Series Econometrics, Spring 2003 Notes Section 9 Panel Unit Root Tests Avariety of procedures for the analysis of unit roots in a panel
EC821: Time Series Econometrics, Spring 2003 Notes Section 9 Panel Unit Root Tests Avariety of procedures for the analysis of unit roots in a panel context have been developed. The emphasis in this development
Introduction To Maple The Structure of Maple A General Introduction to Maple Maple Quick Review Maple Training Introduction, Overview, And The
To Maple The Structure of Maple A General to Maple Maple Quick Review Maple Training, Overview, And The Process Of Mathematical Modeling The Modeling Process Illustrative Examples Discrete Dynamical Models
This chapter reviews properties of regression estimators and test statistics based on
Chapter 12 COINTEGRATING AND SPURIOUS REGRESSIONS This chapter reviews properties of regression estimators and test statistics based on the estimators when the regressors and regressant are difference
Data are sometimes not compatible with the assumptions of parametric statistical tests (i.e. t-test, regression, ANOVA)
BSTT523 Pagano & Gauvreau Chapter 13 1 Nonparametric Statistics Data are sometimes not compatible with the assumptions of parametric statistical tests (i.e. t-test, regression, ANOVA) In particular, data
normality is a basis of the classical multivariate statistical methodology and consequences of departures from these assumptions have not been
INTRODUCTION The articles we would like to present are the result of the 24th Conference 011 Multivariate Statistical Analysis - MSA 2005 organized by the Chair o f Statistical Methods of the University
SEVERAL μs AND MEDIANS: MORE ISSUES. Business Statistics
SEVERAL μs AND MEDIANS: MORE ISSUES Business Statistics CONTENTS Post-hoc analysis ANOVA for 2 groups The equal variances assumption The Kruskal-Wallis test Old exam question Further study POST-HOC ANALYSIS
A Test of Cointegration Rank Based Title Component Analysis.
A Test of Cointegration Rank Based Title Component Analysis Author(s) Chigira, Hiroaki Citation Issue 2006-01 Date Type Technical Report Text Version publisher URL http://hdl.handle.net/10086/13683 Right
Correlation. Engineering Mathematics III
Correlation Correlation Finding the relationship between two quantitative variables without being able to infer causal relationships Correlation is a statistical technique used to determine the degree
Econometric Methods for Panel Data
Based on the books by Baltagi: Econometric Analysis of Panel Data and by Hsiao: Analysis of Panel Data Robert M. Kunst robert.kunst@univie.ac.at University of Vienna and Institute for Advanced Studies
Statistical Methods for Forecasting
Statistical Methods for Forecasting BOVAS ABRAHAM University of Waterloo JOHANNES LEDOLTER University of Iowa John Wiley & Sons New York Chichester Brisbane Toronto Singapore Contents 1 INTRODUCTION AND
US Army Corps of Engineers Nonstationarity Detection Tool User Guide
US Army Corps of Engineers Nonstationarity Detection Tool User Guide User Guide Version 1.2 May 2016 User Manual Update September 2018 U.S. Army Corps of Engineers Climate Preparedness and Resilience Community
Basics of Uncertainty Analysis
Basics of Uncertainty Analysis Chapter Six Basics of Uncertainty Analysis 6.1 Introduction As shown in Fig. 6.1, analysis models are used to predict the performances or behaviors of a product under design.
Basic Statistical Analysis
indexerrt.qxd 8/21/2002 9:47 AM Page 1 Corrected index pages for Sprinthall Basic Statistical Analysis Seventh Edition indexerrt.qxd 8/21/2002 9:47 AM Page 656 Index Abscissa, 24 AB-STAT, vii ADD-OR rule,
An Introduction to Probability Theory and Its Applications
An Introduction to Probability Theory and Its Applications WILLIAM FELLER (1906-1970) Eugene Higgins Professor of Mathematics Princeton University VOLUME II SECOND EDITION JOHN WILEY & SONS Contents I