In regression models with multiplicative error, estimation is often based on either the log-normal or the gamma model. It is well known that the gamma model with constant coefficient of variation and the log-normal model with constant variance give almost the same analysis. This article focuses...

In this paper, the exact form of Fisher information matrix for a four-parameter kappa distribution (K4D) is determined. The K4D is so general that includes a variety of distributions as special cases. The necessary condition for the existence of Fisher information matrix is for k[not equal to]0,...

A systematic way of selecting hyperparameters of the prior on the shape parameter of the generalized extreme value distribution (GEVD) is presented. The optimal selection is based on a Monte Carlo simulation in the generalized maximum likelihood estimation (GMLE) framework. A scaled total misfit...

We consider hypothesis testing with smooth functional data by performing pointwise tests and applying a multiple comparisons procedure. Methods based on general inequalities, such as Bonferroni's method, do not perform well because of the high correlation between observations at nearby points....

Fluorescence spectroscopy has emerged in recent years as an effective way to detect cervical cancer. Investigation of the data preprocessing stage uncovered a need for a robust smoothing to extract the signal from the noise. Various robust smoothing methods for estimating fluorescence emission...

Bounds for even moments of sums of strong mixing random variables are given which extend existing bounds. The method of proof uses simple facts about strong mixing random variables and combinatorial methods. The bound is particularly useful for triangular arrays with entries decreasing in size....

In this note it is shown that the kernel density estimators converge a.s. uniformly on compact subsets of the variable under [alpha]-mixing. In particular, the rates of convergence for the estimators will be investigated to analyze dependency effects.

We consider the asymptotic analysis of penalized likelihood type estimators for generalized nonparametric regression problems in which the target parameter is a vector-valued function defined in terms of the conditional distribution of a response given a set of covariates. A variety of examples...