Singh, S. (2013). A dual problem of calibration of design weights. Statistics: A Journal of Theoretical and Applied Statistics 47 (3),

Transcription

1 Selected Publications: Sarjinder Singh Singh, S. (2013). A dual problem of calibration of design weights. Statistics: A Journal of Theoretical and Applied Statistics 47 (3), Singh, S. (2012). On calibration of design weights using a displacement function. Metrika, 75, Research books/monographs: A New Concept for Tuning Design Weights in Survey Sampling: Jackknifing in Theory and Practice Authors: Sarjinder Singh, Stephen A. Sedory, Maria Rueda, Antonio Arcos and Raghunath Arnab Accepted: Feb 2015 by the publisher ELSEVIER (In press). Singh, S. (2003). Advanced Sampling Theory with Applications: How Michael selected Amy Vol. 1 & 2, pp , Kluwer Academic Publisher, The Netherlands. Textbook: Singh, S. (2006). Thinking Statistically: Elephants Go to School pp.1-676, Kendall/Hunt Publishing Company, Iowa, USA. Other Publications: Singh, H.P., Tailor, R. and Singh, S. (2012). General procedure for estimating the population mean using ranked set sampling. Journal of Simulation and Computation Statistics, ifirst, 2012, 1 15 Singh, H.P., Chandra, P., Grewal, I.S., Singh, S., Chen, C.C. Sedory, S.A., and Kim, J.-M. (2012). Estimation of population ratio, product, and mean using multi-auxiliary information with random non-response. Rivista Statistica (In press) Singh, S., Sedory, S.A, and Kim, Jong-Min (2012). An empirical likelihood estimate of the finite population correlation coefficient. Communications in Statistics: Simulation and Computation (In press). Singh, H.P., Solanki, R.S. and Singh, S. (2012). Estimation of Bowley s coefficient of Skewness in the presence of auxiliary information. Communications in Statistics: Theory and Methods (In press) Singh, S. and Sedory, S.A. (2012). A true simulation study of three estimators at equal protection of respondents in randomized response sampling. Statistica Neerlandica, 66 (4), Arnab, R., Singh, S. and North, D. (2012). Use of two decks of cards in randomized response techniques for complex survey designs. Communications in Statistics-Theory and Methods, 41:16-17,

2 Singh, H.P., Singh, S. and Kim, J.-M. (2012). Some Alternative Classes of Shrinkage Estimators for Scale Parameter of the Exponential Distribution. The Korean Journal of Applied Statistics. (Accepted) Abdelfatah, S., Mazloum, R and Singh, S. (2012). Efficient use of two-stage randomized response procedure. Brazilian Journal of Probability and Statistics (In press). Verma, M.R., Singh, S. And Pandey, R. (2012). Optimum stratification for sensitive quantitative variables using auxiliary information. Journal of the Indian Society of Agricultural Statistics (Accepted). Chen, C.C. and Singh, S. (2012). Esimation of Multinomial Proportions Using Higher Order Moments of Scrambling Variables in Randomized Response Sampling.. J. of Modern Applied Statistical Meth (In press) Singh, S. and Grewal, I.S. (2012). Estimation of finite population variance using partial jackknifing. Journal of the Indian Society of Agricultural Statistics (Accepted). Ahangar, R., Wang, R., Perez, J. and Singh, S. (2010). Extensive study of logistic regression using randomized response sampling. AMSE Journals (In press) Rueda, M., Arcos, A, Arnab, R and Singh, S. (2011). The Rao, Hartley and Cochran scheme with dubious random non-response in survey sampling. Sankhya (In press) Singh, S. (2011). A dual problem of calibration of design weights. Statistics: A Journal of Theoretical and Applied Statistics (In press) Singh, S. and Arnab, R. (2011). On the calibration of design weights. Metron vol. LXIX, n. 2, pp Arnab, R. and Singh, S. (2011). Estimation of Mean of Sensitive Characteristics for Successive Sampling. Communications in Statistics- Theory and Methods (In press) Singh, S. and Sedory, S. A. (2011). Cramer-Rao lower bound of variance in randomized response sampling. Sociological Methods and Research, 40(3) Singh, H.P., Tailor, R, Singh, S. and Kozak, M. (2011). A generalized method of estimation of a population parameter in two-phase and successive sampling. Qual-Quant (DOI: /s x) Singh, S. and Kim, J.K. (2011). A pseudo-empirical log-likelihood estimator using scrambled responses. Statistics and Probability Letters, 81, Singh, S. and Sedory, S. A. (2011). Sufficient Bootstrapping. Computational Statistics and Data Analysis 55(1),

3 Singh, S. (2012). On calibration of design weights using a displacement function. Metrika 75: Pal, S. and Singh, S. (2012). A new unrelated question randomized response model. Statistics: A Journal of Theoretical and Applied Statistics (In press) Land, M., Singh, S, and Sedory, S.A. (2012). Estimation of a rare sensitive attribute using Poisson distribution. Statistics: A Journal of Theoretical and Applied Statistics, 46(3), Abdelfatah, A., Mazloum, R. and Singh, S. (2011). An alternative randomized response model using two decks of cards. Statistica, LXXI (3), Singh, S. (2010). Proposed optimal orthogonal new additive model. Statistica, LXX, 1, Ahangar, R., Singh, S. and Wang, R. (2010). Dynamic behavior of perturbed logistic model. Journal of Combinatorial Mathematics and Combinatorial Computing (JCMCC) 74, Vishwakarma, G.K., Singh, H.P. and Singh, S. (2010). A family of estimators of population mean using multi-auxiliary variate and post-stratification. Nonlinear Analysis: Modelling and Control, 15, 2, Singh, H.P., Tailor, R., Singh, S. and Kim, J.-M. (2011). Estimation of population variance in successive sampling. Quality and Quality, 45(3), pp Farrell, P.J. and Singh, S. (2010). Some contribution to Jackknifing two-phase sampling estimators. Survey Methodology, 36, 1, Arnab, R. and Singh, S. (2010). Variance estimation of a generalized regression predictor. Journal of the Indian Society of Agricultural Statistics, 64(2), Singh, S. and Arnab, R. (2010). Bias-adjustment and calibration of Jackknife variance estimator in the presence of non-response Journal of Statistical Planning and Inference, 140(4), Arnab, R. and Singh, S. (2010). Randomized response techniques: An application to the Botswana AIDS impact survey. Journal of Statistical Planning and Inference, 140(4) Singh, H.P., Singh, S. and Kim, J.-M. (2010). Efficient Use of Auxiliary Variables in Estimating Finite Population Variance in Two-Phase Sampling. Commun. of the Korean Statistical Society,17(2), Singh, S., Rueda, Mari Del Mar and Sanchez-Borrego, Ismael (2010).Random non-response in multi-character surveys. Quality& Quantity, 44, Singh, S. (2009). Saddlestrapping. Nonlinear Analysis: Modelling and Control, 14 (3),

4 Singh, S. and Chen, C. (2009). Utilization of higher order moments of scrambling variables in randomized response sampling. Journal of Statistical Planning and Inference, 139, Singh, S., Singh, H.P., Tailor, R., Allen, J. and Kazak, M. (2009) Estimation of ratio of two finite -population means in the presence of non-response. Commun in Stat-Theory and Methods,38, Singh, S. (2009). A new method of imputation in survey sampling. Statistics: A Journal of Theoretical and Applied Statistics, 43(5), Sidhu, S.S., Bansal, M.L., Kim, J.M. and Singh, S. (2009). Unrelated question model in sensitive multi-character surveys. Korean Communication Journal of Statistics, 16( 1 ), Singh, S. and Valdes, S. (2009). Optimum method of imputation in survey sampling. Applied Mathematical Sciences,3(35), Sidhu, S.S., Tailor, R and Singh, S. (2009). On the estimation of population proportion. Applied Mathematical Sciences, 3(35), Singh, G.N., Priyanka, K., Kim, J.M. and Singh, S. (2009). Estimation of population mean using imputation techniques in sample surveys. Journal of the Korean Statistical Society, (In press). Singh, S., Kim, J.-M. and Grewal, I.S. (2008). Imputing and Jackknifing scrambled responses. Metron, LXVI (2), Singh, H.P., Tailor, R. and Singh, S. and Kim, J.-M. (2008). A modified estimator of population mean using power transformation Statistical Papers, 49: Kozak, M., Zielinski, A. and Singh, S. (2008). Stratified two-stage sampling in domains: Sample allocation between domains, strata and sampling stages. Statistics and Probability Letters, 78: Singh, H.P., Singh, S. and Kozak, M. (2008). A family of estimators of finite-population distribution function using auxiliary information. Acta Appl Math. 104: Book chapters jointly with MS students: Lee, C.S., Sedory, S.A. and Singh, S. (2015).Cramer-Rao lower bounds of variance for estimating two proportions and their overlap by using two-decks of cards. Accepted by ELSEVIER. Su, Cing-Shu, Sedory, S.A. and Singh, S. (2015). Estimation of means of two rare sensitive characteristics. Accepted by ELSEVIER. Johnson, M.L, Sedory, S. and Singh, S. (2015). Incredibly efficient use of a Negative Hypergeometric distribution in randomized response sampling. Accepted by ELSEVIER.

5 Mohamed, C., Sedory, S.A. and Singh, S. (2015). Comparison of different imputing methods for scrambled responses. Accepted by ELSEVIER. Peer Reviewed Publications from MS theses: Lee, Cheon-Sig, Su, Ching-Su, Mondragon, K., Salinas, V.I., Zamora, M.L., Sedory. S.A. and Singh, S. (2015). Comparison of Cramer-Rao lower bounds of variances for at least equal protection of respondents. Statistica Neerlandica (Accepted) Su, Ching-Su, Sedory, S.A. and Singh, S. (2015). Adjusted Kuk s model using two non-sensitive characteristics unrelated to the sensitive characteristic. Communications in Statistics-Theory and Methods (Accepted) Su, Shu-Ching, Sedory, S.A. and Singh, S. (2015). Kuk s model adjusted for protection and efficiency. Sociological Methods and Research, 44(3) Lee, Cheon-Sig, Sedory, S.A. and Singh, S. (2013). Simulated minimum sample sizes for various randomized response models. Communications in Statistics: Sim. and Comp, 42(4), Lee, Cheon-Sig, Sedory, S.A. and Singh, S. (2013). Estimating at least seven measures for qualitative variables using randomized response sampling. Statistics and Probability Letters, 83, Peer Reviewed Publications from Undergraduate Projects: Dykes, Lee, Singh, S., Sedory, S.A. and Luis, V. (2014). Calibrated estimators of population mean for a mail-survey design. Communications in Statistics: Theory and Methods (In press). Gjestvang, C.R and Singh, S. (2006). A new randomized response model. J. R. Statist. Soc., B, 68, Gjestvang, C. and Singh, S. (2007). Forced Quantitative Randomized Response Model: A new device. Metrika, 66, 2, Gestavang, C. and Singh, S. (2009). An improved randomized response model: Estimation of mean. Journal of Applied Statistics,36(12), Odumade, O. and Singh, S. (2008). Generalized forced quantitative randomized response model: A unified approach. Journal of the Indian Society of Agricultural Statistics, 62(3), Odumade, O. and Singh, S. (2009).Efficient use of two decks of cards in randomized response sampling. Commun. Statist.-Theory Meth., 38: Odumade, O. and Singh, S. (2009). Improved Bar-lev, Bobovitch and Boukai randomized response models. Commun. Statist.-Simulation, 38:

6 Odumade, O. and Singh, S. (2010). An alternative to the Bar-lev, Bobovitch and Boukai randomized response model. Sociological Methods and Research, 39: Odumade, O. and Singh, S. (2010). Use of two variables having common mean to improve the Bar-Lev, Bobovitch and Boukai Randomized Response Model. J. of Modern Applied Statistical Meth, 9(2), Stearns, M. and Singh, S. (2008). On the estimation of the general parameter. Computational Statistics and Data Analysis, 52, Joint Statistical Meeting Conference Presentations from MS Theses and Undergraduate Projects: Mohamed, C., Sedory, S.A. and Singh, S. (2015). A fresh imputing survey methodology using sensible constraints on study and auxiliary variables. Presented at the JSM 2015, Seattle. Lee, C.S., Sedory, S.A. and Singh, S. (2015). On estimating at least seven measures using randomized response sampling: Cramer-Rao lower bounds of variances. Presented at the JSM 2015, Seattle. Jayaraj, A., Odumade, O., Sedory, S.A. and Singh, S. (2015). A forced odds ratio (to be equal to one) leads to a new estimator for randomized response sampling. Presented at the JSM 2015, Seattle. Lee, Cheon-Sig, Sedory, S.A. and Singh, S. (2014). Black magic using randomized response techniques. Presented at JSM 2014, Boston. Jayaraj, A., Odumade, O. and Singh, S. (2014). A New Quasi-Empirical Bayes Estimate in Randomized Response Technique. Presented at JSM 2014, Boston. Su,Shu-Ching, Sedory, S.A. and Singh, S. (2013). Kuk s model adjusted for efficiency and protection using two non sensitive questions unrelated to the characteristic of interest. Presented at the JSM 2013, Montreal, Canada, August 3-8, Odumade, O., Arnab, R. and Singh, S. (2012). Post-Stratification Based on the Choice of Use of a Quantitative Randomization Device. Presenting at the JSM 2012, San Diogo, CA. Odumade, O. and Singh, S. (2011). A new optimal estimator of population proportion in randomized response sampling. Presented at the Joint Statistical Meeting, Miami Beach, FL. Odumade, O. and Singh, S. (2006). Generalized forced quantitative randomized response model. Presented at the Joint Statistical Meeting, Seattle, USA. Gjestvang, Chris and Singh, S. (2005). A new randomized response model: Estimation of Mean. Presented at the Joint Statistical Meeting, Minneapolis, USA. Stearns, M. and Singh, S. (2005). A new model assisted chi-square distance function for the

7 calibration of design weights. Presented at Joint Statistical Meeting, MN, USA. MS students supervised at TAMUK: Lee, Cheon-Sig; Su, Ching-Su; Johnson, M.L and Mohamed, C. Undergraduate students supervised from the US: Dykes, Lee; Odumade, O; Gestavang, C. and Stearns, M.