The paper deals with simple and composite hypotheses in statistical models with i.i.d. observations and with arbitrary families dominated by[sigma]-finite measures and parametrized by vector-valued variables. It introduces[phi]-divergence testing statistics as alternatives to the classical ones:...

The problems of estimating parameters of statistical models for categorical data, and testing hypotheses about these models are studied. Asymptotic properties of estimators minimizing [phi]-divergence between theoretical and empirical vectors of means are established. Asymptotic distributions of...

The paper presents asymptotic distributions of [phi]-disparity goodness-of-fit statistics in product multinomial models, under hypotheses and alternatives assuming sparse and nonsparse cell frequencies. The [phi]-disparity statistics include the power divergences of Read and Cressie...

In continuous parametrized models with i.i.d. observations we consider finite quantizations. We study asymptotic properties of the estimators minimizing disparity between the observed and expected frequencies in the quantization cells, and asymptotic properties of the goodness of fit tests...

We consider f-disparities between discrete distributions pn=(pn1,...,pnkn) and their estimates based on relative frequencies in an i.i.d. sample of size n, where is twice continuously differentiable in a neighborhood of 1 with f''(1)[not equal to]0. We derive asymptotic distributions of the...

This paper extends the results of Chen and Wu [1] concerning consistency of M-estimators in the linear regression model. We consider M-estimators defined by [formula] in the general regression model yi = f(xi,[theta] ) + [epsilon]i, where f(x, [theta]) is continuous on a separable metric space X...