Latent Factor Mixed Models

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 |

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 |

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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