Package index • gputools

Pairwise statistics over many variables

Every pair of variables at once, on the GPU.

gpuCor(): Calculate Various Correlation Coefficients With a GPU
gpuCorPairs(): The Strongest Correlations Among Many Variables, With a GPU
gpuAssoc(): Association Scan: Every Column of x Against Every Column of y, With a GPU
gpuTtest(): T-Test Estimator with a GPU
gpuDist(): Compute Distances Between Vectors on a GPU
gpuGranger(): Perform Granger Causality Tests for Vectors on a GPU
gpuMi(): B spline based mutual information

Permutation and Westfall-Young maxT p-values for every test.

gpuCorPerm(): Permutation Tests of Correlations, With a GPU
gpuRowTtest(): Two-Group t Tests of Every Row, With Permutation p-Values on a GPU

gpuHclust(): Perform Hierarchical Clustering for Vectors with a GPU
gpuDistClust(): Compute Distances and Hierarchical Clustering for Vectors on a GPU
gpuKmeans(): K-Means Clustering With a GPU
gpuPrcomp(): Principal Components Analysis on a GPU
gpuSvd(): Singular Value Decomposition on a GPU

The same interface as base R; base R is as fast at most sizes.

gpuLm(): Fitting Linear Models using a GPU–enabled QR
gpuLm.fit(): Fitter functions for gpu enabled linear models
gpuLm.defaultTol(): Function to switch tolerance depending on precision
gpuLsfit(): Least squares fit using GPU–enabled QR decomposition
gpuGlm() gpuGlm.fit(): Fitting generalized linear models using GPU–enabled QR decomposition
gpuQr(): Estimate the QR decomposition for a matrix
gpuSolve(): Estimate the solution to a matrix vector equation
gpuMatMult(): Perform Matrix Multiplication with a GPU
gpuCrossprod(): Perform Matrix Cross-product with a GPU
gpuTcrossprod(): Perform Matrix Transposed Cross-product with a GPU
cpuMatMult(): Perform Matrix Multiplication