Distributional data analysis of accelerometer data from the NHANES database using nonparametric survey regression models

Estimating Distribution Functions from Survey Data Using Nonparametric Regression

Survey sampling often supplies information about a study variable only for sampled elements. However, auxiliary information is often available for the entire population. The relationship of the auxiliary information with the study variable across the sample allows inferences about the nonsampled portion of the population. Thus, auxiliary information can be used to improve upon survey estimation...

A New Nonparametric Regression for Longitudinal Data

In many area of medical research, a relation analysis between one response variable and some explanatory variables is desirable. Regression is the most common tool in this situation. If we have some assumptions for such normality for response variable, we could use it. In this paper we propose a nonparametric regression that does not have normality assumption for response variable and we focus ...

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...

Comparison of time to the event and nonlinear regression models in the analysis of germination data

Extended abstract   Introduction: Numerous studies are being carried out to reveal the effects of different treatments on the germination of seeds from various plants. The most commonly used method of analysis is the nonlinear regression which estimates germination parameters. Although the nonlinear regression has been performed based on different models, some serious problems in its structure...

Nonparametric Regression with Complex Survey Data