Recursive residuals for linear mixed models

Bayesian Inference for Spatial Beta Generalized Linear Mixed Models

In some applications, the response variable assumes values in the unit interval. The standard linear regression model is not appropriate for modelling this type of data because the normality assumption is not met. Alternatively, the beta regression model has been introduced to analyze such observations. A beta distribution represents a flexible density family on (0, 1) interval that covers symm...

Invariance Principles for Recursive Residuals

The Application of Recursive Mixed Models for Estimating Genetic and Phenotypic Relationships between Calving Difficulty and Lactation Curve Traits in Iranian Holsteins: A Comparison with Standard Mixed Models

In the present study, records on 22872 first-parity Holsteins collected from 131 herds by the Animal Breeding and Improvement Center of Iran from 1995 to 2014 were considered to estimate genetic and phenotypic relationships between calving difficulty (CD) and the lactation curve traits, including initial milk yield (Ap), ascending (Bp) and descending (Cp) slope of the lactation curves, peak mil...

Cluster detection based on spatial associations and iterated residuals in generalized linear mixed models.

SUMMARY Spatial clustering is commonly modeled by a Bayesian method under the framework of generalized linear mixed effect models (GLMMs). Spatial clusters are commonly detected by a frequentist method through hypothesis testing. In this article, we provide a frequentist method for assessing spatial properties of GLMMs. We propose a strategy that detects spatial clusters through parameter estim...

Various Recursive Mixed L2-Linfty Algorithms for Linear-in-the-Parameters Models

In this paper, various Recursive Mixed L2-Linfty (RML) learning algorithms are developed by choosing different forgetting factor matrix function () for Linear-inthe-Parameters (LIP) models, including Projection, Recursive Mixed L2-Linfty, Recursive Mixed Mean L2-Linfty, weighted Mixed L2-Linfty, instantaneous RML, and Batch RML algorithms. A few models are given to apply the proposed RML alg...