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Estimation of Proportion of GM Stacked Seeds in Seed Lots
Estimate the percentage of seeds containing GM traits.

Estimating the proportion of genetically modified stacked seeds
in seedlots via multinomial group testing
Estimate the percentage of seeds in a seedlot that contain
stacks of genetically modified traits.  Estimates are
calculated using a multinomial group testing model with maximum
likelihood estimation of the parameters.

Estimate the percentage of seeds in a seedlot that contain stacks
of genetically modified traits.  Estimates are calculated using a
multinomial group testing model with maximum likelihood estimation of the
parameters.

Estimating the Proportion of Genetically Modified Seeds in
Seedlots via Multinomial Group Testing
c(
person("Kevin","Wright", email="kw.stat@gmail.com", role=c("aut","cre")),
person("Jean-Louis","Laffont", role=c("aut")))

Robust Structural Equation Modeling with Missing Data and
Auxiliary Variables
This package estimates means and covariance matrix of
multiple variables with missing data using Huber weight and
then estimates a SEM model using EQS.

This package estimates means and covariance matrix of multiple variables with missing data using Huber weight and then estimates a SEM model using EQS.

This package estimates means and covariance matrix of
multiple variables with missing data using Huber weight and
then estimates a SEM model using lavaan.

This package estimates means and covariance matrix of
multiple variables with missing data using Huber weight and
then estimates a SEM model using lavaan or EQS.

This package estimates means and covariance matrix of multiple variables with missing data using Huber weight and then estimates a SEM model using lavaan or EQS.

A robust procedure is implemented to estimate means and covariance matrix of multiple variables with missing data using Huber weight and then to estimate a structural equation model.