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asremlPlus (version 4.2-26)

Augments 'ASReml-R' in Fitting Mixed Models and Packages Generally in Exploring Prediction Differences

Description

Assists in automating the selection of terms to include in mixed models when 'asreml' is used to fit the models. Also used to display, in tables and graphs, predictions obtained using any model fitting function and to explore differences between predictions. The content falls into the following natural groupings: (i) Data, (ii) Object manipulation functions, (iii) Model modification functions, (iv) Model testing functions, (v) Model diagnostics functions, (vi) Prediction production and presentation functions, (vii) Response transformation functions, and (viii) Miscellaneous functions (for further details see 'asremlPlus-package' in help). A history of the fitting of a sequence of models is kept in a data frame. Procedures are available for choosing models that conform to the hierarchy or marginality principle and for displaying predictions for significant terms in tables and graphs. The 'asreml' package provides a computationally efficient algorithm for fitting mixed models using Residual Maximum Likelihood. It is a commercial package that can be purchased from 'VSNi' as 'asreml-R', who will supply a zip file for local installation/updating (see ). It is not needed for functions that are methods for 'alldiffs' and 'data.frame' objects. The package 'asremPlus' can also be installed from .

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Version

Install

install.packages('asremlPlus')

Monthly Downloads

1,155

Version

4.2-26

License

MIT + file LICENSE

Maintainer

Chris Brien

Last Published

November 11th, 2020

Functions in asremlPlus (4.2-26)

alldiffs.object

Description of an alldiffs object
Oats.dat

Data for an experiment to investigate nitrogen response of 3 oats varieties
changeModelOnIC.asrtests

Uses information criteria to decide whether to change an already fitted model.
REMLRT.asreml

Performs a REML ratio test to compare two models.
angular

Applies the angular transformation to proportions.
getASRemlVersionLoaded

Finds the version of asreml that is loaded and returns the initial characters in version.
getFormulae.asreml

Gets the formulae from an asreml object.
getTestPvalue.asrtests

bootREMLRT.asreml

Uses the parametric bootstrap to calculate the p-value for a REML ratio test to compare two models.
infoCriteria

Computes AIC and BIC for models.
plotPredictions.data.frame

Plots the predictions for a term, possibly with error bars.
as.asrtests

Forms an asrtests object that stores (i) a fitted asreml object, (ii) a pseudo-anova table for the fixed terms and (iii) a history of changes and hypthesis testing used in obtaining the model.
plotPvalues.alldiffs

Plots a heat map of p-values for pairwise differences between predictions.
print.alldiffs

angular.mod

Applies the modified angular transformation to a vector of counts.
as.alldiffs

Forms an alldiffs.object from the supplied predictions, along with those statistics, associated with the predictions and their pairwise differences, that have been supplied.
testranfix.asrtests

WaterRunoff.dat

Data for an experiment to investigate the quality of water runoff over time
print.asrtests

testresidual.asrtests

variofaces.asreml

Plots empirical variogram faces, including envelopes, as described by Stefanova, Smith & Cullis (2009).
asremlPlusTips

The randomly-presented, startup tips.
Wheat.dat

Data for a 1976 experiment to investigate 25 varieties of wheat
facRecode.alldiffs

Recodes factor levels using values in a vector. The values in the vector do not have to be unique.
asrtests.object

Description of an asrtests object
linTransform.alldiffs

facRename.alldiffs

Renames factors in the prediction component of an alldiffs.object.
addBacktransforms.alldiffs

as.predictions.frame

Forms a predictions.frame from a data.frame, ensuring that the correct columns are present.
chooseModel.asrtests

Determines and records the set of significant terms using an asrtests.object, taking into account the hierarchy or marginality relations of the terms.
chooseModel.data.frame

estimateV.asreml

Forms the estimated variance, random or residual matrix for the observations from the variance parameter estimates.
allDifferences.data.frame

Using supplied predictions and standard errors of pairwise differences or the variance matrix of predictions, forms all pairwise differences between the set of predictions, and p-values for the differences.
asremlPlus-deprecated

Deprecated Functions in the Package asremlPlus
plotPvalues.data.frame

Plots a heat map of p-values for pairwise differences between predictions.
recalcLSD.alldiffs

ChickpeaEnd.dat

A large data set comprising the end of imaging data from a chick pea experiment conducted in high-throughtput greenhouses
recalcWaldTab.asrtests

Recalculates the denDF, F.inc and P values for a table of Wald test statistics obtained using wald.asreml
testswapran.asrtests

is.predictions.frame

Tests whether an object is of class predictions.frame
loadASRemlVersion

Ensures that a specific version of asreml is loaded.
iterate.asrtests

Subject the fitted asreml.obj stored in an asrtests.object to further iterations of the fitting process.
facCombine.alldiffs

plotVariofaces.data.frame

Plots empirical variogram faces, including envelopes, from supplied residuals as described by Stefanova, Smith & Cullis (2009).
powerTransform

Performs a combination of a linear and a power transformation on a variable. The transformed variable is stored in the data.frame data.
validAlldiffs

Checks that an object is a valid alldiffs object.
is.alldiffs

Tests whether an object is of class alldiffs
Ladybird.dat

Data for an experiment to investigate whether ladybirds transfer aphids
permute.to.zero.lowertri

Permutes a square matrix until all the lower triangular elements are zero.
asremlPlus-package

asremlPlus
changeTerms.asrtests

Adds and drops the specified sets of terms from one or both of the fixed or random model and/or replaces the residual (rcov) model with a new model.
predictPlus.asreml

Forms the predictions for a term, their pairwise differences and associated statistics. A factor having parallel values may occur in the model and a linear transformation of the predictions can be specified. It results in an object of class alldifffs.
permute.square

Permutes the rows and columns of a square matrix.
is.asrtests

Tests whether an object is of class asrtests
print.test.summary

Prints a data.frame containing a test.summary.
print.predictions.frame

Prints the values in a predictions.frame, with or without title and heading.
redoErrorIntervals.alldiffs

chooseModel

renewClassify.alldiffs

Renews the components in an alldiffs.object according to a new classify.
simulate.asreml

Produce sets of simulated data from a multivariate normal distribtion and save quantites related to the simulated data
newfit.asreml

Refits an asreml model with modified model formula using either a call to update.asreml or a direct call to asreml.
setvarianceterms.call

allows the setting of bounds and initial values for terms in the random and residual arguments of an asreml call, with the resulting call being evaluated.
validAsrtests

Checks that an object is a valid asrtests object.
validPredictionsFrame

Checks that an object is a valid predictions.frame.
subset.alldiffs

Subsets the components in an alldiffs.object according to the supplied condition.
predictPresent.asreml

Forms the predictions for each of one or more terms and presents them in tables and/or graphs.
num.recode

Recodes the unique values of a vector using the values in a new vector.
sort.alldiffs

Sorts the components in an alldiffs.object according to the predicted values associated with a factor.
printFormulae.asreml

Prints the formulae from an asreml object.
print.wald.tab

Prints a data.frame containing a Wald or pseudoanova table.
reparamSigDevn.asrtests

Reparamterizes each random (deviations) term involving devn.fac to a fixed term and ensures that the same term, with trend.num replacing devn.fac, is included if any other term with trend.num is included in terms.
rmboundary.asrtests

predictions.frame

Description of a predictions object