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krm (version 2022.10-17)

Kernel Based Regression Models

Description

Implements several methods for testing the variance component parameter in regression models that contain kernel-based random effects, including a maximum of adjusted scores test. Several kernels are supported, including a profile hidden Markov model mutual information kernel for protein sequence. This package is described in Fong et al. (2015) .

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Install

install.packages('krm')

Monthly Downloads

214

Version

2022.10-17

License

GPL-2

Maintainer

Youyi Fong

Last Published

October 18th, 2022

Functions in krm (2022.10-17)

hmmMargLlik

Functions related to profile HMM
cloud9

9-Component Mixture Dirichlet Prior for Protein Sequences
dmdirichlet

Functions related to mixture Dirichlet distribution
calcPairwiseIdentity

Functions Related to Sequence Alignment
getSeqKernel

Protein Sequence Kernels
chi.norm

A Transformation of Chi-squared Random Variable
aa.prop.list

Amino Acid Properties
krm.most

Kernel-based Regression Model Maximum of adjusted Score Test
krm.score.test

Adjusted Score Test
krm package

Kernel-based Regression Models
readFastaFile

Read a Fasta Sequence File
sim.liu.2008

Simulate sDataset