est {qgen}R Documentation

estimating parameters from data sets

Description

estimates variance components for random effects and coefficients of the fixed effects for a given paraDATA–object.

Usage

est(paraDATA, file=TRUE, path="~/qgen/")

Arguments

paraDATA list with a definded structure; see paraDATA
file Logical flag: Should the paraDATA object be written to path/"est.rda"?
path indicating the path where the file est.rda should be written

Details

The parameters of the the and the emp function determine the estimations that are performed and the exact structure of the output

Value

a paraDATA–object:

orig full
supl full
para full, with phS=NULL
spec depending on the supl-slot of the paraDATA and on the history of the object itself:
unbal
information on the unbalacedness of the data; different degrees of freedom:
xxDF
normal degrees of freedom
xxDFappREML
Satterthwaite approximated degrees of freedom using the REML variance components
xxDFappANOVA
Satterthwaite approximated degrees of freedom using the ANOVA estimators for variance components
xxDFappANOVAuw
Satterthwaite approximated degrees of freedom using the ANOVA estimators with unweighted sums of squares for variance components
weights used to calculate the expected mean squares
w1u
for dam variance in calculation of sire mean square
w2u
for sire variance
w3u
for dam variance in calculation of dam mean square
modelsummary
additional information:
sBLUP
the best linear unbiased predictors for the sire effect
modelsumry
the summary(lme4-object)
secondcontrast
the same model with a different contrast matrix to estimate the difference in on character between environments:
FIX
an array with the means of all fixed effects
modelsumry2
the summary(lme4-object) for a second model estimated with contrast for testing whether a character differs between two environments
secondpartitioning
variance components additionally (to REML) estimated by:
ANOVA
estimators (normal):
rbS
variance component for factor sire
siS
variance component for factor sire
daS
variance component for factor dam
idS
variance component for residuals
phS
NULL
error
0; the model residuals are included in the idS
ANOVAuw
estimators based on unweighted sums of squares (for balanced data equal to ANOVA):
rbS
variance component for factor sire
siS
variance component for factor sire
daS
variance component for factor dam
idS
variance component for residuals
phS
NULL
error
0; the model residuals are included in the idS

Note

name:est from estimation

References

Burdick, R. K. and Graybill, F. A. (1992) Confidence intervals on variance components. Marcel Dekker.

Sen, B., Graybill, F. A. and Ting, N. (1992) Confidence intervals on variance components. Biometrical Journal 3, 259–274.

See Also

paraDATA

Examples

parameters <- est(sim(the(file=FALSE)), file=FALSE)
   # takes the default causal parameters of the()
   # simulates a data set
   # estimates the parameters

[Package qgen version 0.03-02 Index]