boot.lm | Sampling of linear model parameters using bootstrap method. |
calibration.mad | calibrate zscore with mad estimator of variance |
gwas.linearmodel | X = mu + G_j * B + epsilon |
gwas.linearmodel.ridge | X = G * B + epsilon + regularisation ridge |
lfmm.ml.ridge | LFMM with ridge likelihood |
lfmm.ml.ridge2 | LFMM with ridge likelihood implementation 2 |
lfmm.ml.ridge2.lr | LFMM with ridge likelihood implementation 2 + LR for score |
lfmm.ml.ridge2.normalization | LFMM with ridge likelihood implementation 2 + normalization |
lfmm.ml.ridge3 | LFMM with ridge likelihood implementation 3 |
linear_model | only LM |
sample.binary.model | Sample P(G) = logistic(mu + UV^T + XB^T + e) |
sample.normal.model | Sample G = mu + UV^T + XB^T + e |
sample.phenotype | Sample Phenotype = Somme(B_j * G_j) + epsilon Same simulation... |
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