R: Statistical Inference for Unsupervised Learning

# Statistical Inference for Unsupervised Learning

## Documentation for package ‘jackstraw’ version 1.3.21

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

jackstraw-package | jackstraw: Statistical Inference for Unsupervised Learning
find_k | Find a number of clusters or principal components
jackstraw | jackstraw: Statistical Inference for Unsupervised Learning
jackstraw_alstructure | Non-Parametric Jackstraw for ALStructure
jackstraw_cluster | Jackstraw for the User-Defined Clustering Algorithm
jackstraw_irlba | Non-Parametric Jackstraw for Principal Component Analysis (PCA) using the augmented implicitly restarted Lanczos bidiagonalization algorithm (IRLBA)
jackstraw_kmeans | Non-Parametric Jackstraw for K-means Clustering
jackstraw_kmeanspp | Non-Parametric Jackstraw for K-means Clustering using RcppArmadillo
jackstraw_lfa | Non-Parametric Jackstraw for Logistic Factor Analysis
jackstraw_MiniBatchKmeans | Non-Parametric Jackstraw for Mini Batch K-means Clustering
jackstraw_pam | Non-Parametric Jackstraw for Partitioning Around Medoids (PAM)
jackstraw_pca | Non-Parametric Jackstraw for Principal Component Analysis (PCA)
jackstraw_rpca | Non-Parametric Jackstraw for Principal Component Analysis (PCA) using Randomized Singular Value Decomposition
jackstraw_subspace | Jackstraw for the User-Defined Dimension Reduction Methods
Jurkat293T | A Jurkat:293T equal mixture dataset from Zheng et al. (2017)
ncp_est | Estimate parameter of non-central Chi squared distributed data
permutationPA | Permutation Parallel Analysis
pip | Compute posterior inclusion probabilities (PIPs)
pvals_nc_chisq | Calculate high precision p-values from Jackstraw data under non-central chi squared distribution for null statistics