I. Csiszár's (Magyar. Tud. Akad. Mat. Kutató Int. Közl8 (1963), 85-108) [phi]-divergence, which was considered independently by M. S. Ali and S. D. Silvey (J. R. Statist. Soc. Ser. B28 (1966), 131-142) gives a goodness-of-fit statistic for multinomial distributed data. We define a generalized...

Trimmed best k-nets were introduced in J. A. Cuesta-Albertos, A. Gordaliza and C. Matrán (1998, Statist. Probab. Lett.36, 401-413) as a robustified L[infinity]-based quantization procedure. This paper focuses on the asymptotics of this procedure. Also, some possible applications are briefly...

Continuity of procedures based on the halfspace (Tukey) depth (location and regression setting) is investigated in the framework of continuity concepts from set-valued analysis. Investigated procedures are depth contours (upper level sets) and maximum depth estimators. Continuity is studied both...

Let X be an d-valued random variable with unknown density f. Let X1, ..., Xn be i.i.d. random variables drawn from f. The objective is to estimate f(x), where x=(x1, ..., xd). We study the pointwise convergence of two new density estimates, the Hilbert product kernel estimate where...

In this paper we consider measurement error models when the observed random vectors are independent and have mean vector and covariance matrix changing with each observation. The asymptotic behavior of the sample mean vector and the sample covariance matrix are studied for such models. Using the...

We derive simpler expressions under a certain structure of design matrices for the two-stage Aitken estimates of the regression coefficients of two seemingly unrelated regression equations. The estimates are shown to have smaller variance than the ordinary least squares estimates for...

We consider testing the validity of the generalized logit model with I+1 categories based on case-control data. After reparametrization, the assumed logit model is equivalent to an (I+1)-sample semiparametric model in which the I log ratios of two unspecified density functions are linear in...

We consider the problem of discriminating between two independent multivariate normal populations, Np([mu]1, [Sigma]1) and Np([mu]2, [Sigma]2), having distinct mean vectors [mu]1 and [mu]2 and distinct covariance matrices [Sigma]1 and [Sigma]2. The parameters [mu]1, [mu]2, [Sigma]1, and...

We develop Bayesian methods for right censored multivariate failure time data for populations with a cure fraction. We propose a new model, called the multivariate cure rate model, and provide a natural motivation and interpretation of it. To create the correlation structure between the failure...

This paper deals with the problem of Stein-rule prediction in a general linear model. Our study extends the work of Gotway and Cressie (1993) by assuming that the covariance matrix of the model's disturbances is unknown. Also, predictions are based on a composite target function that...