Search Results:

Showing results 1 to 10 of 389.


Function is.fullrank [limma v3.28.14]
keywords
algebra
title
Check for Full Column Rank
description
Test whether a numeric matrix has full column rank.
Function get.eigentraits [cape v2.0.2]
keywords
algebra
title
Calculate eigentraits from phenotype matrix
description
This function performs the singular value decomposition (SVD) on the phenotype matrix after first removing individuals with missing data. The eigentraits are the left singular vectors of the decomposition. This function optionally mean centers and normalizes the phenotype matrix before performing the SVD.
Function projections [lspls v0.2-2]
keywords
algebra
title
Projection and Orthogonalisation
description
Functions to project one matrix onto another, or to ortghogonalise it against the other.
Function make.del [mvnmle v0.1-11.1]
keywords
algebra
title
Make the upper triangular matrix del from a parameter vector
description
make.del takes a parameter vector of length \(k*(k+1)/2\) and returns the upper triangular \(k \times k\) matrix \(\Delta\). make.del is a private function intended for use inside mlest.
Function tr [lmreg v1.2]
keywords
algebra
title
Trace of matrix
description
Computes the trace of a given matrix.
Function my.positive.definite.solve [pendensity v0.2.13]
keywords
algebra
title
my.positive.definite.solve
description
Reverses a quadratic positive definite matrix.
Function tab.disjonctif [FactoMineR v2.2]
keywords
algebra
title
Make a disjonctif table
description
Make a disjonctif table.
Function tab.disjonctif.prop [FactoMineR v2.2]
keywords
algebra
title
Make a disjunctive table when missing values are present
description
Create a disjunctive table. The missing values are replaced by the proportion of the category.
Function svd.triplet [FactoMineR v2.2]
keywords
algebra
title
Singular Value Decomposition of a Matrix
description
Compute the singular-value decomposition of a rectangular matrix with weights for rows and columns.
Function dimcalc [lsa v0.73.2]
keywords
algebra
title
Dimensionality Calculation Routines (LSA)
description
Methods for choosing a `good' number of singular values for the dimensionality reduction in LSA.