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evolqg (version 0.3-4)

Evolutionary Quantitative Genetics

Description

Provides functions for covariance matrix comparisons, estimation of repeatabilities in measurements and matrices, and general evolutionary quantitative genetics tools. Melo D, Garcia G, Hubbe A, Assis A P, Marroig G. (2016) .

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Version

Install

install.packages('evolqg')

Monthly Downloads

508

Version

0.3-4

License

MIT + file LICENSE

Maintainer

Last Published

December 5th, 2023

Functions in evolqg (0.3-4)

LocalShapeVariables

Local Shape Variables
ExtendMatrix

Control Inverse matrix noise with Extension
MantelCor

Compare matrices via Mantel Correlation
ComparisonMap

Generic Comparison Map functions for creating parallel list methods Internal functions for making eficient comparisons.
Center2MeanJacobianFast

Centered jacobian residuals
JacobianArray

Local Jacobian calculation
CalcRepeatability

Parametric per trait repeatabilities
CalcEigenVar

Integration measure based on eigenvalue dispersion
CalcICV

Calculates the ICV of a covariance matrix.
DeltaZCorr

Compare matrices via the correlation between response vectors
BootstrapRep

Bootstrap analysis via resampling
CalculateMatrix

Calculate Covariance Matrix from a linear model fitted with lm()
DriftTest

Test drift hypothesis
MonteCarloR2

R2 confidence intervals by parametric sampling
MINT

Modularity and integration analysis tool
MonteCarloRep

Parametric repeatabilities with covariance or correlation matrices
PlotTreeDriftTest

Plot results from TreeDriftTest
PlotRarefaction

Plot Rarefaction analysis
RSProjection

Random Skewers projection
RandCorr

Random correlation matrix
KrzSubspaceDataFrame

Extract confidence intervals from KrzSubspaceBootstrap
Rarefaction

Rarefaction analysis via resampling
LModularity

L Modularity
EigenTensorDecomposition

Eigentensor Decomposition
KrzCor

Compare matrices via Krzanowski Correlation
MonteCarloStat

Parametric population samples with covariance or correlation matrices
MatrixCompare

Matrix Compare
MantelModTest

Test single modularity hypothesis using Mantel correlation
KrzSubspace

Krzanowski common subspaces analysis
SingleComparisonMap

Generic Single Comparison Map functions for creating parallel list methods Internal functions for making efficient comparisons.
MultiMahalanobis

Calculate Mahalonabis distance for many vectors
KrzSubspaceBootstrap

Quasi-Bayesian Krzanowski subspace comparison
PCScoreCorrelation

PC Score Correlation Test
TPS

TPS transform
RarefactionStat

Non-Parametric rarefacted population samples and statistic comparison
Partition2HypotMatrix

Create binary hypothesis
Rotate2MidlineMatrix

Midline rotate
SRD

Compare matrices via Selection Response Decomposition
MeanMatrix

Mean Covariance Matrix
MatrixDistance

Matrix distance
PhyloMantel

Mantel test with phylogenetic permutations
PlotKrzSubspace

Plot KrzSubspace boostrap comparison
PhyloCompare

Compares sister groups
PhyloW

Calculates ancestral states of some statistic
KrzProjection

Compare matrices via Modified Krzanowski Correlation
MeanMatrixStatistics

Calculate mean values for various matrix statistics
RelativeEigenanalysis

Relative Eigenanalysis
MultivDriftTest

Multivariate genetic drift test for 2 populations
Normalize

Normalize and Norm
PrintMatrix

Print Matrix to file
RemoveSize

Remove Size Variation
RevertMatrix

Revert Matrix
ProjectMatrix

Project Covariance Matrix
RiemannDist

Matrix Riemann distance
OverlapDist

Distribution overlap distance
dentus

Example multivariate data set
dentus.tree

Tree for dentus example species
PCAsimilarity

Compare matrices using PCA similarity factor
evolqg

EvolQG
RandomMatrix

Random matrices for tests
RandomSkewers

Compare matrices via RandomSkewers
ratones

Linear distances for five mouse lines
TestModularity

Test modularity hypothesis
TreeDriftTest

Drift test along phylogeny
AlphaRep

Alpha repeatability
BayesianCalculateMatrix

Calculate Covariance Matrix from a linear model fitted with lm() using different estimators
BootstrapStat

Non-Parametric population samples and statistic comparison
CalcAVG

Calculates mean correlations within- and between-modules
CreateHypotMatrix

Creates binary correlation matrices
BootstrapR2

R2 confidence intervals by bootstrap resampling
CalcR2

Mean Squared Correlations
CalcR2CvCorrected

Corrected integration value