Man pages for bcm-uga/MatrixFactorizationR
Latent Factor Mixed Models

compute_PCompute the matrix used to reduce correlation with X
compute_pvalue_from_tscorescore are assume to follow student distibution with df degre...
compute_pvalue_from_zscorescore are assume to follow normal distibution
DatClass which store data
effect_sizeDirect effect sizes estimated from latent factor models
example.dataGenetic and phenotypic data for Arabidopsis thaliana
forward_testForward inclusion tests with latent factor mixed models
glm_testGLM tests with latent factor mixed models
hypothesis_testing_lmHypothesis testing with lm
left.out.kfoldreturn a list of train/test indices
lfmmR package with matrix factorization algorithms
lfmm_CVCross validation
LfmmDatClass which store data
lfmm_fitFit the model
lfmm_fit_knowing_loadingsFit the model when latent factor loadings are known
lfmm_fit_knowing_loadings.ridgeLFMMFit assuming V and B
lfmm_imputeImpute Y with a fitted model.
lfmm_lassoLFMM least-squares estimates with lasso penalty
lfmm_residual_error2Compute the residual error
lfmm_ridgeLFMM least-squares estimates with ridge penalty
lfmm_ridge_CVCross validation of LFMM estimates with ridge penalty
lfmm_samplerLFMM generative data sampler
lfmm_testStatistical tests with latent factor mixed models (linear...
predict_lfmmPredict polygenic scores from latent factor models
SimulatedLfmmDatClass which store data
skin.exposureSimulated (and real) methylation levels for sun exposed...
bcm-uga/MatrixFactorizationR documentation built on May 7, 2019, 1:29 p.m.