We examine the performance of asymptotic inference as well as bootstrap tests for the Alphabeta and Kobus-Mi±o´s family of inequality indices for ordered response data. We use Monte Carlo experiments to compare the empirical size and statistical power of asymptotic inference and the...

We examine the performance of asymptotic inference as well as bootstrap tests for the Alphabeta and Kobus-Miłoś family of inequality indices for ordered response data. We use Monte Carlo experiments to compare the empirical size and statistical power of asymptotic inference and the Studentized...

We propose two families of maximally selected phi-divergence tests for studying change point locations when the unknown probability vectors of a sequence of multinomial random variables, with possibly different sizes, are piecewise constant. In addition, these test-statistics are valid to...

Inequality indices for self-assessed health and life satisfaction are typically constructed as functions of the cumulative distribution function. We present a unified methodology for the estimation of the resulting inequality indices. We also obtain explicit standard error formulas in the...

Diagnostics have not received much attention in the literature of simple correspondence analysis models. Since Cook’s distance was defined to identify influential observations of the linear regression model, it has been extended to different models, in particular to log-linear models. In this...

We propose two families of maximally selected phi-divergence tests to detect a change in the probability vectors of a sequence of multinomial random variables with possibly different sizes. In addition, the proposed statistics can be used to estimate the location of the change-point. We derive...