In the economics and biological gene expression study area where a large number of variables will be involved, even when the predictors are independent, as long as the dimension is high, the maximum sample correlation can be large. Variable selection is a fundamental method to deal with such...

Partially linear models are extended linear models where one covariate is nonparametric, which is a good balance between flexibility and parsimony. The partially linear stochastic model with heteroscedastic errors is considered, where the nonparametric part can act as a trend. The estimators of...

In survival studies, current status data are frequently encountered when some individuals in a study are not successively observed. This paper considers the problem of simultaneous variable selection and parameter estimation in the high-dimensional continuous generalized linear model with...

Consider the probability of random time absolute ruin in the renewal risk model with constant premium rate and constant force of interest. We assume that claim sizes Xi,i=1,2,…, are conditionally independent on some sigma algebra and that the common distribution belongs to class D∩L. We...

In this paper, we study a stationary ARCH(q) model with parameters &agr;_0,&agr;_1,&agr;_2, H ,&agr;_q. It is known that the model requires all parameters &agr;_i to be non-negative, but sometimes the usual algorithm based on Newton-Raphson's method leads us to obtain some negative solutions. So this study proposes...

In this paper, we propose a method for constructing a new class of copulas. They are called linear B-spline copulas which are a good approximation of a given complicated copula by using finite numbers of values of this copula without the loss of some essential properties. Moreover, rigorous...

Consider a risk model with two correlated classes of insurance business and a constant force of interest. We assume that the correlation comes from a common shock and that the claim-size distribution is heavy-tailed. Under this setting, we investigate the tail behavior of the sum of the two...

Variable selection is fundamental to high dimensional generalized linear models. A number of variable selection approaches have been proposed in the literature. This paper considers the problem of variable selection and estimation in generalized linear models via a bridge penalty in the...

This paper considers a partially nonlinear model , which is a sub-model of the general partially nonlinear model but has some particular advantages in statistical inference. We develop a sieve least squares method to estimate the parameters of the parametric part and the nonparametric part. The...