The common approach to SNP genotyping is to use (model-based) clustering per individual SNP, on a set of arrays. Genotyping all SNPs on a single array is much more attractive, in terms of flexibility, stability and applicability, when developing new chips. A new semi-parametric method, named SCALA, is proposed. It is based on a mixture model using semi-parametric log-concave densities. Instead ...

Considerable previous literature has addressed the problem of finding the most desirable estimator of the long memory parameter in a univariate time series. This paper considers three different estimation procedures: (i) the long memory parameter is obtained from a semi parametric Local Whittle estimator, which is used to filter the series before estimation of the short run parameters, (ii) a t...

The objective of hazards (lifetime) analysis is to advance and promote statistical science in the various applied fields that deal with lifetime (survival) data including: actuarial science and reliability engineering. The lifetime data analysis provides special techniques that are required to compare the risks for failure. Bayesian semi-parametric methods have been applied to survival analysis...

Linear regression models are widely used in mental health and related health services research. However, the classic linear regression analysis assumes that the data are normally distributed, an assumption that is not met by the data obtained in many studies. One method of dealing with this problem is to use semi-parametric models, which do not require that the data be normally distributed. But...

We study the problem of optimizing over parameters a particular real root of a polynomial with parametric coefficients. We propose an efficient symbolic method for solving the optimization problem based on a special cylindrical algebraic decomposition algorithm, which asks for a semi-algebraic decomposition into cells in terms of Number-of-Roots-invariant. Mathematics Subject Classification (20...

PURPOSE To evaluate a semi-parametric, model-based approach for obtaining transcription rates from mRNA and protein expression. METHODS The transcription profile input was modeled using an exponential function of a cubic spline and the dynamics of translation; mRNA and protein degradation were modeled using the Hargrove-Schmidt model. The transcription rate profile and the translation, and mR...

We study the asymptotic distribution of three-step estimators of a …nite dimensional parameter vector where the second step consists of one or more nonparametric regressions on a regressor that is estimated in the …rst step. The …rst step estimator is either parametric or non-parametric. Using Newey’s (1994) path-derivative method we derive the contribution of the …rst step estimator to the in‡...

In many biomedical studies, it is of interest to assess dependence between bivariate failure time data. We focus here on a special type of such data, referred to as semi-competing risks data. In this article, we develop methods for making inferences regarding dependence of semi-competing risks data across strata of a discrete covariate Z. A class of rank statistics for testing constancy of asso...

This paper discusses the simultaneous inference of mean parameters in a family of distributions with quadratic variance function. We first introduce a class of semi-parametric/parametric shrinkage estimators and establish their asymptotic optimality properties. Two specific cases, the location-scale family and the natural exponential family with quadratic variance function, are then studied in ...

Background:Brucellosis or Malta fever is one of the most common zoonotic diseases in the world. In addition to causing human suffering and dire economic impact on animals, due to the high prevalence of Brucellosis in the western regions of Isfahan province, this study aimed to analyze effective factors in the time of Brucellosis diagnosis using parametric and semi-parametric mo...