This paper provides higher-order improvements over the delta method of coverage probability errors of parametric bootstrap confidence intervals (CIs) for the covariance parameters of a time series ...

Usually, there are residual deviations from the estimated model relationship, and such deviations commonly show a pattern of phylogenetic correlations indicating that they have biological causes. We ...

Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.

10.3.1 Scatterplot matrix Recall that we use SAS’s scatterplot matrix feature to quickly scan for pairs of explanatory variables that might be colinear. To do this in R we must first make sure we ...

Nonlinear regression is a form of regression analysis in which data fit to a model is expressed as a mathematical function.

The least squares (OLS) residuals are often used to construct test statistics; in order to overcome the non-independent and identically residuals, the best linear unbiased scale (BLUS) residuals are ...

Abstract Objectives: The objective is to analyze the interaction of the correlation structure and values of the regressor variables in the estimation of a linear model when there is a constant, ...