Modelling temporal genetic and spatio‐temporal residual effects for high‐throughput phenotyping data*

DOI10.1111/anzs.12336zbMath1521.62206OpenAlexW3186861670MaRDI QIDQ6051630

Unnamed Author, Joanne De Faveri, Arūnas P. Verbyla, Unnamed Author

Publication date: 20 October 2023

Published in: Australian & New Zealand Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/anzs.12336

zbMATH Keywords

linear mixed modelgenetic modelsHTPresidual modelsfactor analytic modelsreduced rank tensor spline

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

• Unnamed Item
• Unnamed Item
• Efficient two-dimensional smoothing with \(P\)-spline ANOVA mixed models and nested bases
• Straightforward intermediate rank tensor product smoothing in mixed models
• That BLUP is a good thing: The estimation of random effects. With comments and a rejoinder by the author
• Tensor cubic smoothing splines in designed experiments requiring residual modelling
• Residual variance-covariance modelling in analysis of multivariate data from variety selection trials
• Analyzing Variety by Environment Data Using Multiplicative Mixed Models and Adjustments for Spatial Field Trend
• An Approach to the Analysis of Repeated Measurements
• The Analysis of Designed Experiments and Longitudinal Data by Using Smoothing Splines
• Bayesian inference for variance components using only error contrasts
• A note on model selection using information criteria for general linear models estimated using REML
• Recovery of inter-block information when block sizes are unequal