[Statlist] Reminder: ETH/UZH Research Seminar on Statistics by Cun-Hui Zhang, Rutgers University, USA, 21.08.2023

[Maurer Letizia]

We are glad to announce the following talk in the ETH/UZH Research Seminar on Statistics: 

"Chi-Squared and Normal Approximations in Large Contingency Tables"   

by Cun-Hui Zhang, Rutgers University, USA

Time: Monday,  21.08.2023 at 16.00 h
Place: ETH Zurich, HG G 26.5

Abstract: We provide necessary and su cient conditions for the chi-squared and normal approximations of Pearson's chi-squared statistics for the test of independence and the goodness-of- t test, as well as necessary and sufficient conditions for the normal approximation of the likelihood ratio and Hellinger statistics, when the cell probabilities of the multinomial data are in general pattern and the dimension diverges with the sample size. A cross-sample chi-squared statistic for testing independence applies to two-way contingency tables with diverging dimensions. A degrees-of-freedom adjusted chi-squared approximation applies continuously throughout the high-dimensional regime and matches Pearson's chi-squared statistic in both the mean and variance. Specific examples are provided to demonstrate the asymptotic normality of the three types of test statistics when the classical regularity conditions for the chi-squared and normal approximations are violated. Simulation results demonstrate that the chi-squared and normal approximations are more robust for the likelihood ratio and Hellinger statistics, compared with Pearson's chi-squared statistics. This talk is based on joint work with Chong Wu and Yisha Yao.

Seminar website: https://math.ethz.ch/sfs/news-and-events/research-seminar.html

Research Seminar – Seminar for Statistics | ETH Zurich
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