Statistical scientists have recently focused sharp attention on properties of iterated chaotic maps, with a view to employing such processes to model naturally occurring phenomena. In the present paper we treat the logistic map, which has earlier been studied in the context of modelling...

This note is concerned with estimating censored quantile regressions (CQR). As its major contribution, a' new algorithm, called BRCENS, is developed as an adaption of the Barrodale-Roberts algorithm for the standard quantile regression problem. In a subsequent simulation study, BRCENS performs...

This note is concerned with estimating censored quantile regressions (CQR). As its major contribution, a' new algorithm, called BRCENS, is developed as an adaption of the Barrodale-Roberts algorithm for the standard quantile regression problem. In a subsequent simulation study, BRCENS performs...

This note is concerned with estimating censored quantile regressions (CQR). As its major contribution, a' new algorithm, called BRCENS, is developed as an adaption of the Barrodale-Roberts algorithm for the standard quantile regression problem. In a subsequent simulation study, BRCENS performs...

Likelihood-based cross-validation is a statistical tool for selecting a density estimate based on n i.i.d. observations from the true density among a collection of candidate density estimators. General examples are the selection of a model indexing a maximum likelihood estimator, and the...

Likelihood-based cross-validation is a statistical tool for selecting a density estimate based on n i.i.d. observations from the true density among a collection of candidate density estimators. General examples are the selection of a model indexing a maximum likelihood estimator, and the...

Local polynomial fitting for univariate data has been widely studied and discussed, but up until now the multivariate equivalent has often been deemed impractical, due to the so-called curse of dimensionality. Here, rather than discounting it completely, we use density as a threshold to...

We suggest two improved methods for conditional density estimation. The rst is based on locally tting a log-linear model, and is in the spirit of recent work on locally parametric techniques in density estimation. The second method is a constrained local polynomial estimator. Both methods always...