DUBLIN, Ireland--(BUSINESS WIRE)--Research and Markets (http://www.researchandmarkets.com/reports/c81986) has announced the addition of “Linear Models in Statistics ...

"First edition published in 2006." 1. Introduction -- What are linear mixed models (LMMs)? -- Models with random effects for clustered data -- Models for longitudinal or repeated-measures data -- A ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

With modern technology development, functional responses are observed frequently in fields such as biology, meteorology, and ergonomics, among others. Consider statistical inferences for functional ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

ABSTRACT The interest in climate prediction has seen a rise in the number of modeling alternatives in recent years. One way to reduce the predictive uncertainty from any such modeling procedure is to ...