Estimation after selection from bivariate normal population with application to poultry feeds data

Estimation Using Bivariate Extreme Ranked Set Sampling With Application To The Bivariate Normal Distribution

Estimation of Count Data using Bivariate Negative Binomial Regression Models

Abstract Negative binomial regression model (NBR) is a popular approach for modeling overdispersed count data with covariates. Several parameterizations have been performed for NBR, and the two well-known models, negative binomial-1 regression model (NBR-1) and negative binomial-2 regression model (NBR-2), have been applied. Another parameterization of NBR is negative binomial-P regression mode...

Bivariate Density Estimation with an Application to Survival Analysis

A procedure for estimating a bivariate density based on data that may be censored is described After the data are transformed to the unit square the bivariate density is estimated using linear splines and their tensor products The combined procedure yields an estimate of the bivariate density on the original scale which may provide insight about the dependence structure The procedure can also b...

Sieve Estimation with Bivariate Interval Censored Data

Bivariate interval censored data arises in many applications. However, both theoretical and computational investigations for this type of data are limited because of the complicated structure of bivariate censoring. In this paper, we propose a two-stage spline-based sieve estimator for the association between two event times with bivariate case 2 interval censored data. A smooth and explicit es...

cient Estimation in the Bivariate Normal Copula

Consider semiparametric bivariate copula models in which the family of copula functions is parametrized by a Euclidean parameter of interest and in which the two unknown marginal distributions are the in nite dimensional nuisance parameters The e cient score for can be characterized in terms of the solutions of two coupled Sturm Liouville equations In case the family of copula functions corresp...