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Rfast (version 1.7.3)

Fast R Functions

Description

A collection of fast (utility) functions for data analysis. Column- and row- wise means, medians, variances, minimums, maximums, many t, F and G-square tests, many regressions (normal, logistic, Poisson), Mahalanobis distance are some of the many fast functions.

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Version

Install

install.packages('Rfast')

Monthly Downloads

27,461

Version

1.7.3

License

GPL-2

Maintainer

Manos Papadakis

Last Published

December 18th, 2016

Functions in Rfast (1.7.3)

Column and rows-wise mean absolute deviations

Column and row-wise mean absolute deviations
Equality of objects

Equality of objects
Column and row-wise means of a matrix

Column and row-wise means of a matrix
MLE of the Beta distribution

MLE of the Beta distribution
Binary search algorithm

Binary search algorithm
Column and row-wise medians

Column and row-wise medians
Many multi-sample tests

Many multi-sample tests
Floyd-Warshall algorithm

Floyd-Warshall algorithm for shortest paths in a directed graph
Correlations

Correlation between a vector and a set of variables
Column and row-wise variances and standard deviations

Column and row-wise variances and standard deviations of a matrix
All k possible combinations from n elements

All k possible combinations from n elements
Count the frequency of a value

Count the frequency of a value
Covariance and correlation matrix

Fast covariance and correlation matrix calculation
Design Matrix

Design Matrix
Fitting a Dirichlet distribution via Newton-Rapshon

Fitting a Dirichlet distribution via Newton-Rapshon
Distance between vectors and a matrix

Distance between vectors and a matrix
Hash - Pair function

Hash - Pair function
Find the given value in a hash table

Find the given value in a hash table
Median of a vector

Median of a vector
Match

Match
Many univariate simple binary logistic regressions

Many univariate simple binary logistic regressions
Mahalanobis distance

Mahalanobis distance
Find element

Find element
Natural logarithm of the gamma function and its derivatives

Sorting of the columns of a matrix
Matrix with G-square tests of indepedence

G-square test of indepdence
G-square test of conditional indepdence

G-square test of conditional indepdence
The nth largest value of a vector

The nth largest value of a vector
Rfast-package

Really fast R functions
Many univariate simple linear regressions

Many univariate simple linear regressions
Order

Order
Permutation

Permutation
Many univariate simple poisson regressions

Many univariate simple poisson regressions
Multivariate Laplace random values simulation

Multivariate Laplace random values simulation
Multivariate normal and t random values simulation

Multivariate normal and t random values simulation
Many 2 sample t-tests

Many 2 sample tests t-tests
Many univariate generalised linear models

Many univariate generalised linear regressions
Sort a vector coresponding to another

Sort
MLE of the zero inflated and zero truncated Poisson

MLE of the zero inflated and zero truncated Poisson
Index of the columns of a data.frame which are factor variables

Index of the columns of a data.frame which are factor variables
Sorting of the columns of a matrix

Sorting of the columns of a matrix
Many multivariate simple linear regressions coefficients

Many multivariate simple linear regressions coefficients
minimum and maximum

Minimum and maximum of a vector
Row-wise minimum and maximum

Row-wise minimum and maximum of a matrix.
Sort and unique numbers

Sort and unique
Many score based GLM regressions

Many score based GLM regressions
Standardisation

Standardisation
Angular central Gaussian random values simulation

Angular central Gaussian random values simulation
Many 2 sample proportions tests

Many 2 sample proportions tests
Column and row-wise sums of a matrix

Column and row-wise sums of a matrix
Column and row-wise range of values of a matrix

Column and row-wise range of values of a matrix.
Column-wise minimum and maximum

Column-wise minimum and maximum of a matrix
Many simple linear regressions coefficients

Simple linear regressions coefficients