compute_P | Compute the matrix used to reduce correlation with X |
compute_pvalue_from_tscore | score are assume to follow student distibution with df degre... |
compute_pvalue_from_zscore | score are assume to follow normal distibution |
Dat | Class which store data |
effect_size | Direct effect sizes estimated from latent factor models |
example.data | Genetic and phenotypic data for Arabidopsis thaliana |
forward_test | Forward inclusion tests with latent factor mixed models |
glm_test | GLM tests with latent factor mixed models |
hypothesis_testing_lm | Hypothesis testing with lm |
left.out.kfold | return a list of train/test indices |
lfmm | R package with matrix factorization algorithms |
lfmm_CV | Cross validation |
LfmmDat | Class which store data |
lfmm_fit | Fit the model |
lfmm_fit_knowing_loadings | Fit the model when latent factor loadings are known |
lfmm_fit_knowing_loadings.ridgeLFMM | Fit assuming V and B |
lfmm_impute | Impute Y with a fitted model. |
lfmm_lasso | LFMM least-squares estimates with lasso penalty |
lfmm_residual_error2 | Compute the residual error |
lfmm_ridge | LFMM least-squares estimates with ridge penalty |
lfmm_ridge_CV | Cross validation of LFMM estimates with ridge penalty |
lfmm_sampler | LFMM generative data sampler |
lfmm_test | Statistical tests with latent factor mixed models (linear... |
predict_lfmm | Predict polygenic scores from latent factor models |
SimulatedLfmmDat | Class which store data |
skin.exposure | Simulated (and real) methylation levels for sun exposed... |
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