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chickn (version 1.2.3)

'Compressive' Hierarchical Kernel Clustering Toolbox

Description

Routines for efficient cluster analysis of large scale data. This package implements the 'CHICKN' clustering algorithm (see 'Permiakova' 'et' 'al.' (2020) "'CHICKN': Extraction of 'peptide' 'chromatographic' 'elution' profiles from large scale mass 'spectrometry' data by means of 'Wasserstein' 'compressive' hierarchical cluster analysis"). Functions for data compression, hierarchical clustering and post processing are provided.

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Version

Install

install.packages('chickn')

Monthly Downloads

36

Version

1.2.3

License

GPL (>= 2)

Maintainer

Olga Permiakova

Last Published

November 24th, 2020

Functions in chickn (1.2.3)

Chromatogram Hierarchical Compressive K-means with Nystrom approximation

Euclidean distance

GenerateFrequencies

Frequency vector construction

Data variance estimation

Compressive Orthogonal Matching Pursuit with Replacement

Draw frequency vectors

Objective function

Nystrom kernel approximation

Parallel computation of the Wasserstein distances between cluster centroid and points in the cluster

Computation of the Wasserstein distances between cluster centroids

Parallel computation of the Wasserstein distances between cluster centroids

Gradient_OMP_cpp

Gradient and objective function

Computation of the Wasserstein distances between cluster centroid and signals in the cluster

cumsum_parallel

Cumulative sum computation

Wasserstein-1 distance

big_parallelize

big_parallelize

W1_cl_centr_BIG

W1_cl_centr_BIG

gamma_estimation

Kernel parameter estimation

W1_centr_centr_BIG

Parallel computation for big clusters of the Wasserstein distances between cluster centroids