# Fast R Functions

## Documentation for package ‘Rfast’ version 1.7.5

- DESCRIPTION file.

## Help Pages

Rfast-package | Really fast R functions
allbetas | Simple linear regressions coefficients
all_equals | Equality of objects
anovas | Many multi-sample tests
beta.mle | MLE of the Beta distribution
binary_search | Binary search algorithm
check_data | Search for variables with zero range in a matrix
colhameans | Column and row-wise means of a matrix
colMads | Column and row-wise mean absolute deviations
colMaxs | Column-wise minimum and maximum of a matrix
colmeans | Column and row-wise means of a matrix
colMedians | Column and row-wise medians
colMins | Column-wise minimum and maximum of a matrix
colMinsMaxs | Column-wise minimum and maximum of a matrix
colrange | Column and row-wise range of values of a matrix.
colsums | Column and row-wise sums of a matrix
colVars | Column and row-wise variances and standard deviations of a matrix
comb_n | All k possible combinations from n elements
cor.fsreg | Correlation based forward regression.
cora | Fast covariance and correlation matrix calculation
correls | Correlation between a vector and a set of variables
count_value | Count the frequency of a value
cova | Fast covariance and correlation matrix calculation
data.frame.to_matrix | Convert a dataframe to matrix
design_matrix | Design Matrix
Digamma | Natural logarithm of the gamma function and its derivatives.
diri.nr2 | Fitting a Dirichlet distribution via Newton-Rapshon
Dist | Distance matrix
dista | Distance between vectors and a matrix
floyd | Floyd-Warshall algorithm for shortest paths in a directed graph
ftests | Many multi-sample tests
g2Test | G-square test of conditional indepdence
g2Test_perm | G-square test of conditional indepdence
g2Test_univariate | G-square test of indepdence
g2Test_univariate_perm | G-square test of indepdence
hash.find | Find the given value in a hash table
hash.list | Hash - Pair function
is.symmetric | Check whether a square matrix is symmetric
is_element | Find element
Lgamma | Natural logarithm of the gamma function and its derivatives.
logistic_only | Many univariate simple binary logistic regressions
mahala | Mahalanobis distance
Match | Match
med | Median of a vector
min_max | Minimum and maximum of a vector
mvbetas | Many multivariate simple linear regressions coefficients
negbin.mle | MLE of count data
nth | The nth smallest value of a vector
Order | Order
permutation | Permutation
permutation.next | Permutation
permutation.prev | Permutation
poisson_only | Many univariate simple poisson regressions
proptests | Many 2 sample proportions tests
racg | Angular central Gaussian random values simulation
regression | Many univariate simple linear regressions
rmvlaplace | Multivariate Laplace random values simulation
rmvnorm | Multivariate normal and t random values simulation
rmvt | Multivariate normal and t random values simulation
rowhameans | Column and row-wise means of a matrix
rowMaxs | Row-wise minimum and maximum of a matrix.
rowmeans | Column and row-wise means of a matrix
rowMedians | Column and row-wise medians
rowMins | Row-wise minimum and maximum of a matrix.
rowrange | Column and row-wise range of values of a matrix.
rowsums | Column and row-wise sums of a matrix
rowVars | Column and row-wise variances and standard deviations of a matrix
score.betaregs | Many score based Beta regressions
score.glms | Many score based GLM regressions
score.multinomregs | Many score based GLM regressions
score.negbinregs | Many score based negative binomial regressions
score.weibregs | Many score based Weibull regressions
sort_cor_vectors | Sort
sort_index | Sort
sort_mat | Sorting of the columns of a matrix
sort_unique | Sort and unique
spat.med | Spatial median for Euclidean data
standardise | Standardisation
Trigamma | Natural logarithm of the gamma function and its derivatives.
ttests | Many 2 sample tests t-tests
univglms | Many univariate generalised linear regressions
Var | Variance of a vector
weibull.mle | MLE of the Weibull distribution
which_isFactor | Index of the columns of a data.frame which are factor variables
zip.mle | MLE of count data
ztp.mle | MLE of count data