pesel - Automatic Estimation of Number of Principal Components in PCA
Automatic estimation of number of principal components in PCA with PEnalized SEmi-integrated Likelihood (PESEL). See Piotr Sobczyk, Malgorzata Bogdan, Julie Josse 'Bayesian dimensionality reduction with PCA using penalized semi-integrated likelihood' (2017) <doi:10.1080/10618600.2017.1340302>.
Last updated 4 years ago
4.35 score 5 stars 3 dependents 10 scripts 258 downloadsvarclust - Variables Clustering
Performs clustering of quantitative variables, assuming that clusters lie in low-dimensional subspaces. Segmentation of variables, number of clusters and their dimensions are selected based on BIC. Candidate models are identified based on many runs of K-means algorithm with different random initializations of cluster centers.
Last updated 4 years ago
4.32 score 3 stars 14 scripts 158 downloadsgeneSLOPE - Genome-Wide Association Study with SLOPE
Genome-wide association study (GWAS) performed with SLOPE, short for Sorted L-One Penalized Estimation, a method for estimating the vector of coefficients in linear model. In the first step of GWAS, SNPs are clumped according to their correlations and distances. Then, SLOPE is performed on data where each clump has one representative.
Last updated 3 years ago
4.18 score 3 stars 7 scripts 195 downloads