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Fit linear mixed models using advanced Residual Maximum Likelihood (REML) techniques in an R environment

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Harness the power of REML using R

ASReml-R is powerful statistical software specially designed for mixed models using Residual Maximum Likelihood (REML) to estimate the parameters in an R environment. Linear mixed effects models provide a rich and flexible tool for the analysis of many data sets commonly arising in animal, plant and aqua breeding, agriculture, environmental sciences and medical sciences.

Features of ASReml-R

Balanced and unbalanced longitudinal data
Balanced and unbalanced longitudinal data
Repeated measures data (multivariate analysis of variance and spline type models)
Repeated measures data (multivariate analysis of variance and spline type models)
Multi-environment trials and meta analysis
Multi-environment trials and meta analysis
Univariate and multivariate animal breeding and genetics data (involving a relationship matrix for correlated effects)
Univariate and multivariate animal breeding and genetics data (involving a relationship matrix for correlated effects)
Regular or irregular spatial data
Regular or irregular spatial data

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Our analytics and consulting services are used across the globe by seed, plant, aqua and animal breeding companies, helping them develop new varieties, strains, stocks and breeds.
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