TY - JOUR T1 - Adaptive thresholding estimator for differential association structures in two independent contingency tables AU - Ghoreishi, Seyed Kamran AU - Wu, Jingjing PY - 2020 DA - August DO - 10.15672/hujms.560405 JF - Hacettepe Journal of Mathematics and Statistics PB - Hacettepe University WT - DergiPark SN - 2651-477X SP - 1480 EP - 1492 VL - 49 IS - 4 LA - en AB - In this paper, we consider an adaptive thresholding procedure to estimate the difference of association structures in two independent two-way contingency tables of the same order. Here, we assume that the class of paired association structures have an approximately sparse difference. Under $L_1$ and $L_2$ loss functions, we establish the corresponding risk's upper bounds for our differential association adaptive thresholding estimators. Moreover, we show that these estimators perform well in a simulated setting. In this line, we carry out a simulation study and compare two well-known independent social mobility datasets. KW - Association orthogonal components KW - Intrinsic association parameters KW - Adaptive thresholding estimator KW - sparsity CR - [1] A. Agresti, Categorical Data Analysis, J. Wiley, Hoboken, New Jersey, 2002. CR - [2] F. Bartolucci and A. Forcina, Extended RC association models allowing for order restrictions and marginal modeling, J. Amer. Statist. Associ., 97, 1192-1199, 2002. CR - [3] M.P. Becker and A. Agresti, Maximum likelihood estimation of the RC(M) association model, Appl. Statist., 39, 152-167, 1992. CR - [4] M.P. Becker and C. Clogg, Analysis of sets of two-way contingency tables using association models, J. Amer. Statist. Asso., 84, 142-151, 1989. CR - [5] Y.M. Bishop, S.E. Fienberg, and P.W. Holland, Discrete Multivariate Analysis: Theory and Applications, Springer, 2007. CR - [6] V.V. Buldygin and V.Y. Kozachnko, Subgaussian random variables, Ukrainian Math. J., 32, 483-489, 1980. CR - [7] T.T. Cai and A. Zhang, Inferencial for high-dimensional differential correlation matrices, J. of Multivariate Analysis, 143, 107-126, 2016. CR - [8] T.T. Cai and H.H. Zhou, Optimal rates of convergence for sparse covariance matrix estimation, Ann. Statist., 40(5), 2389-2420 2012. CR - [9] S.K. Ghoreishi and M.R. Meshkani, Bayesian analysis of association (BANOAS) in contingency tables with ordinal and interval variables, J. of Statistical Theory and Applications, 5(2), 363-372, 2006. CR - [10] S.K. Ghoreishi and M.R. Meshkani, Asymptotic Maximum Likelihood and Bayesian Analysis of Shares of Various Weighted Trends in Association Models in Contingency Tables, J. of Statistical Theory and Applications, 7(2), 229-243, 2008. CR - [11] L.O. Goodman, Simple models for the analysis of association in cross-classifications having ordered categories, J. Amer. Statist. Associ., 74, 537-552, 1979. CR - [12] L.O. Goodman, The analysis of cross-classified data having ordered and/or unordered categories: association models, correlation models and asymmetry models for contingency tables with or without missing entries, Ann. statist., 13, 10-69, 1985. CR - [13] L.O. Goodman, Measures, models, and graphical displays in the analysis of crossclassified data, J. Amer. Statist. Assoc., 86, 1085-1111, 1991. CR - [14] M. Kateri, T. Papaioannou, and R. Ahmad, New association models for the analysis of sets of two-way contingency tables, Statistica Applica, 8, 537-551, 1996. CR - [15] M. Kateri, R. Ahmad, and T. Papaioannou, New features in the class of association models, Applied Stochastic models and Data Analysis, 14, 125-136, 1998. CR - [16] A. Rothman, E. Levina, and J. Zhu, Generalized thresholding of large covariance matrices, J. Amer. Statist. Associ., 104, 177-186, 2009. UR - https://doi.org/10.15672/hujms.560405 L1 - https://dergipark.org.tr/en/download/article-file/1229871 ER -