| A Collection of Efficient and Extremely Fast R Functions | Rfast-package |
| All k possible combinations from n elements | comb_n |
| Analysis of covariance | ancova1 |
| Analysis of variance with a count variable | geom.anova poisson.anova quasipoisson.anova |
| Angular central Gaussian random values simulation | racg |
| ANOVA for two quasi Poisson regression models | anova_quasipois.reg |
| Apply method to Positive and Negative number | negative positive positive.negative |
| Apply to each column a method under condition | apply.condition |
| Backward selection regression | bs.reg |
| BIC (using partial correlation) forward regression | bic.corfsreg |
| BIC forward regression with generalised linear models | bic.fs.reg |
| Binary search algorithm | binary_search |
| Binomial coefficient and its logarithm | Choose Lchoose |
| Bootstrap t-test for 2 independent samples | boot.ttest2 |
| Check if any column or row is fill with values | colrow.value |
| Check if values are integers and convert to integer | as_integer is_integer |
| Check Namespace and Rd files | checkAliases checkExamples checkNamespace checkTF checkUsage |
| Check whether a square matrix is symmetric | is.symmetric |
| Chi-square and G-square tests of (unconditional) indepdence | gchi2Test |
| Cholesky decomposition of a square matrix | cholesky |
| Circular or angular regression | spml.reg |
| Circular-linear correlation | circlin.cor |
| Coefficient matrices. | coeff |
| Colum-wise cumulative operations (sum, prod, min, max) | colCumMaxs colCumMins colCumProds colCumSums |
| Column and row wise coefficients of variation | colcvs rowcvs |
| Column and row-wise Any | colAll colAny rowAll rowAny |
| Column and row-wise means of a matrix | colhameans colmeans colmeans.data.frame colmeans.matrix rowhameans rowmeans |
| Column and row-wise medians of a matrix or median of a vector. | colMedians med Median rowMedians |
| Column and row-wise nth smallest value of a matrix/vector | colnth nth rownth |
| Column and row-wise Order - Sort Indices | colOrder Order rowOrder |
| Column and row-wise products | colprods rowprods |
| Column and row-wise range of values of a matrix. | colrange rowrange |
| Column and row-wise ranks | colRanks Rank rowRanks |
| Column and row-wise Shuffle | colShuffle rowShuffle |
| Column and row-wise sums of a matrix | colsums rowsums |
| Column and row-wise tabulate | colTabulate rowTabulate |
| Column and row-wise variances and standard deviations of a matrix | colVars colVars.data.frame colVars.matrix rowVars |
| Column and row-wise mean absolute deviations | colMads Mad rowMads |
| Column-wise differences | coldiffs |
| Column-wise kurtosis and skewness coefficients | colkurtosis colskewness |
| Column-wise matching coefficients | match.coefs |
| Column-wise minimum and maximum of a matrix | colMaxs colMins colMinsMaxs |
| Column-wise MLE of some univariate distributions | colexp2.mle colexpmle colgammamle colinvgauss.mle collaplace.mle collindley.mle colmaxboltz.mle colnormal.mle colnormlog.mle colpareto.mle colrayleigh.mle colvm.mle colweibull.mle |
| Column-wise true/false value of a matrix | colFalse colTrue colTrueFalse |
| Column-wise uniformity tests for circular data | colwatsons |
| Column-wise Yule's Y (coefficient of colligation) | col.yule |
| Convert a dataframe to matrix | data.frame.to_matrix |
| Convert R function to the Rfast's coresponding | as.Rfast.function |
| Correlation based forward regression. | cor.fsreg |
| Correlation between pairs of variables | corpairs |
| Correlation between a vector and a set of variables | correls groupcorrels |
| Fast covariance and correlation matrix calculation | cora cova |
| Cox confidence interval for the ratio of two Poisson variables | col.coxpoisrat cox.poisrat |
| Cross-Validation for the k-NN algorithm | knn.cv |
| Cross-Validation for the k-NN algorithm using the arc cosinus distance | dirknn.cv |
| Deep copy | env.copy |
| Density of the multivariate normal and t distributions | dmvnorm dmvt |
| Design Matrix | design_matrix |
| Diagonal Matrix | Diag.fill Diag.matrix |
| Distance between vectors and a matrix - Sum of all pairwise distances in a distance matrix. | dista total.dista |
| Distance correlation | bcdcor dcor |
| Distance matrix - Sum of all pairwise distances in a distance matrix | Dist total.dist vecdist |
| Distance variance and covariance | dcov dvar |
| Eigenvalues in high dimensional principal component analysis | hd.eigen |
| Empirical and exponential empirical likelihood tests for one sample | eel.test1 el.test1 |
| Empirical and exponential empirical likelihood tests for two samples | eel.test2 el.test2 |
| Energy distance between matrices | edist |
| Equality of objects | all_equals |
| Estimation of an AR(1) model | ar1 colar1 |
| Estimation of the Box-Cox transformation | bc |
| Exact t-test for 2 independent samples | exact.ttest2 |
| Exponential empirical likelihood for a one sample mean vector hypothesis testing | mv.eeltest1 |
| Exponential empirical likelihood hypothesis testing for two mean vectors | mv.eeltest2 |
| Fast and general represantation of a factor variable | print.ufactor ufactor [.ufactor |
| FBED variable selection method using the correlation | cor.fbed |
| Find element | is_element |
| Find the given value in a hash table | hash.find |
| Fitted probabilities of the Terry-Bradley model | btmprobs |
| Fitting a Dirichlet distribution via Newton-Rapshon | diri.nr2 |
| Floyd-Warshall algorithm for shortest paths in a directed graph | floyd |
| Variable selection in generalised linear regression models with forward selection | fs.reg |
| G-square test of conditional indepdence | chi2Test g2Test g2Test_perm |
| Gamma regression with a log-link | gammacon gammareg |
| Gaussian regression with a log-link | normlog.reg |
| Generates random values from a normal and puts them in a matrix | matrnorm |
| Get specific columns/rows fo a matrix | columns rows |
| Hash - Pair function | hash.list |
| Hash object | Hash Hash.key.multi length.Hash print.Hash [.Hash [<-.Hash |
| Hash object to a list object | hash2list |
| High dimensional MCD based detection of outliers | rmdp |
| Hypothesis test for the distance correlation | dcor.ttest |
| Hypothesis test for two means of percentages | percent.ttest |
| Hypothesis test for von Mises-Fisher distribution over Kent distribution | fish.kent |
| Hypothesis testing between two skewness or kurtosis coefficients | kurt.test2 skew.test2 |
| Index of the columns of a data.frame which are a specific type | which.is |
| Insert/remove function names in/from the NAMESPACE file | AddToNamespace RemoveFromNamespace |
| Inverese Gaussian regression with a log-link | invgauss.reg |
| Inverse of a symmetric positive definite matrix | spdinv |
| Iterator | !=.iterator ==.iterator Elem Elem.iterator Elem<- Elem<-.iterator iterator print.iterator |
| James multivariate version of the t-test | james |
| k nearest neighbours algorithm (k-NN) | knn |
| k-NN algorithm using the arc cosinus distance | dirknn |
| Limited number of eigenvalues and eigenvectors of a symmetric matrix | eigen.sym |
| Linear models for large scale data | lmfit |
| Logistic and Poisson regression models | glm_logistic glm_poisson |
| Logistic or Poisson regression with a single categorical predictor | logistic.cat1 poisson.cat1 |
| Lower and Upper triangular of a matrix | lower_tri lower_tri.assign upper_tri upper_tri.assign |
| Mahalanobis distance | mahala |
| Many area under the curve values | auc colaucs |
| Many 2 sample proportions tests | proptests |
| Many 2 sample tests tests | mcnemars ttests var2tests |
| Many analysis of variance tests with a discrete variable | geom.anovas poisson.anovas quasipoisson.anovas |
| Many ANCOVAs | ancovas |
| Many ANOVAS for count data with Poisson or quasi Poisson models | colpoisson.anovas colquasipoisson.anovas |
| Many exponential regressions | expregs |
| Many F-tests with really huge matrices | list.ftests |
| Many G-square tests of indepedence | chi2tests g2tests g2tests_perm |
| Many Gini coefficients | ginis |
| Many hypothesis tests for two means of percentages | percent.ttests |
| Many moment and maximum likelihood estimations of variance components | colvarcomps.mle colvarcomps.mom |
| Many multi-sample tests | anovas block.anovas ftests vartests |
| Many multivariate simple linear regressions coefficients | mvbetas |
| Many multi-sample tests | cqtests kruskaltests |
| Many odds ratio tests | odds |
| Many one sample goodness of fit tests for categorical data | cat.goftests |
| Many one sample tests | proptest ttest vartest |
| Many random intercepts LMMs for balanced data with a single identical covariate | colrint.regbx |
| Many regression based tests for single sample repeated measures | rm.anovas rm.lines |
| Many score based regressions | score.betaregs score.expregs score.gammaregs score.geomregs score.glms score.invgaussregs score.multinomregs score.negbinregs score.weibregs score.ztpregs |
| Many Shapiro-Francia normality tests | sftest sftests |
| Many simple circular or angular regressions | spml.regs |
| Many simple geometric regressions. | geom.regs |
| Many simple linear mixed model regressions | rint.regs |
| Simple linear regressions coefficients | allbetas |
| Many simple multinomial regressions. | multinom.regs |
| Many simple regressions for positive valued data | gammaregs invgauss.regs normlog.regs |
| Many tests for the dispersion parameter in Poisson distribution | colpois.tests colpoisdisp.tests |
| Many two-way ANOVAs | twoway.anovas |
| Many univariate generalised linear regressions | univglms univglms2 |
| Many univariate simple linear regressions | regression |
| Many univariate simple binary logistic regressions | logistic_only poisson_only |
| Many univariate simple poisson regressions | quasi.poisson_only |
| Many Welch's F-tests | colanovas |
| Match | Match |
| Matrix multiplication, Cross and Tcross product. | Crossprod mat.mult Tcrossprod |
| Matrix with all pairs of t-tests | allttests ttests.pairs |
| Matrix with G-square tests of indepdence | chi2Test_univariate g2Test_univariate g2Test_univariate_perm |
| Minima and maxima of two vectors/matrices and Column-row wise minima and maxima of two matrices | colPmax colPmin Pmax Pmin Pmin_Pmax |
| Minimum and maximum of a vector | min_max |
| Minimum and maximum frequencies of a vector | freq.max freq.min |
| MLE for multivariate discrete data | colgeom.mle colpoisson.mle dirimultinom.mle multinom.mle |
| MLE of (hyper-)spherical distributions | acg.mle iag.mle multivmf.mle vmf.mle |
| MLE of continuous univariate distributions defined on the positive line | betaprime.mle chisq.mle exp2.mle expmle foldnorm.mle gammamle halfnorm.mle invgauss.mle lindley.mle logcauchy.mle loglogistic.mle lognorm.mle lomax.mle maxboltz.mle normlog.mle pareto.mle rayleigh.mle weibull.mle |
| MLE of continuous univariate distributions defined on the real line | cauchy.mle ct.mle gumbel.mle laplace.mle logistic.mle normal.mle tmle wigner.mle |
| MLE of count data | betabinom.mle betageom.mle binom.mle borel.mle geom.mle logseries.mle negbin.mle poisson.mle zip.mle ztp.mle |
| MLE of distributions defined in the (0, 1) interval | beta.mle hsecant01.mle ibeta.mle logitnorm.mle |
| MLE of some circular distributions | spml.mle vm.mle wrapcauchy.mle |
| MLE of the inverted Dirichlet distribution | invdir.mle |
| MLE of the multivariate (log-) normal distribution | mvlnorm.mle mvnorm.mle |
| MLE of the multivariate t distribution | mvt.mle |
| MLE of the ordinal model without covariates | ordinal.mle |
| MLE of the tobit model | tobit.mle |
| Moment and maximum likelihood estimation of variance components | rint.mle varcomps.mle varcomps.mom |
| Multi-sample tests for vectors | anova1 block.anova cqtest ftest kruskaltest mcnemar ttest2 twoway.anova var2test |
| Multinomial regression | multinom.reg |
| Multivariate kurtosis | mvkurtosis |
| Multivariate Laplace random values simulation | rmvlaplace |
| Multivariate normal and t random values simulation | rmvnorm rmvt |
| Naive Bayes classifiers | gammanb gaussian.nb geom.nb multinom.nb poisson.nb |
| Natural Logarithm each element of a matrix | Log |
| Natural logarithm of the beta function | Lbeta |
| Natural logarithm of the gamma function and its derivatives. | Digamma Lgamma Trigamma |
| Norm of a matrix | Norm |
| Number of equal columns between two matrices | mat.mat |
| Odds ratio and relative risk | odds.ratio rel.risk |
| One sample t-test for a vector | ttest1 |
| Operations between two matrices or matrix and vector | eachcol.apply eachrow XopY.sum |
| Orthogonal matching pursuit variable selection | omp ompr |
| Outer function | Outer |
| Permutation | bincomb permutation permutation.next permutation.prev |
| Permutation based p-value for the Pearson correlation coefficient | permcor |
| Polyserial correlation | poly.cor |
| Pooled covariance matrix | pooled.cov |
| Prediction with some naive Bayes classifiers | gammanb.pred gaussiannb.pred geomnb.pred multinomnb.pred poissonnb.pred |
| Quasi binomial regression for proportions | prop.reg prop.regs |
| Quasi Poisson regression | qpois.reg qpois.regs |
| Random intercepts linear mixed models | rint.reg rint.regbx |
| Random values simulation from a von Mises distribution | rvonmises |
| Reading the files of a directory | read.directory read.examples |
| Repeated measures anova | rm.anova |
| Replicate columns/rows | rep_col rep_row |
| Represantation of Stack | Stack |
| Round each element of a matrix/vector | Round |
| Row - Wise matrix/vector count the frequency of a value | colCountValues count_value rowCountValues |
| Row-wise minimum and maximum of a matrix. | rowMaxs rowMins rowMinsMaxs |
| Row-wise true value of a matrix | rowFalse rowTrue rowTrueFalse |
| Search for variables with zero range in a matrix | check_data |
| Significance testing for the coefficients of Quasi binomial or the quasi Poisson regression | anova_propreg anova_qpois.reg |
| Simulating from a Bingham distribution | rbing |
| Simulation of random values from a Bingham distribution with any symmetric matrix | rbingham |
| Simulation of random values from a normal distribution | Rnorm |
| Random values simulation from a von Mises-Fisher distribution | rvmf |
| The skeleton of a Bayesian network produced by the PC algorithm | pc.skel |
| Skewness and kurtosis coefficients | kurt skew |
| Some summary statistics of a vector for each level of a grouping variable. | group group.sum |
| Sort - Integer Sort - Sort a vector coresponding to another | Sort Sort.int sort_cor_vectors |
| Sort and unique | sort_unique sort_unique.length |
| Sorting of the columns-rows of a matrix | colSort rowSort sort_mat |
| Source many R files | sourceR sourceRd |
| Spatial median for Euclidean data | spat.med |
| Spatial median regression | spatmed.reg |
| Spatial sign covariance matrix | sscov |
| Fast calculation of the spherical and hyperspherical median | mediandir |
| Standardisation | standardise |
| Sub-matrix | submatrix |
| Table Creation - Frequency of each value | Table Table.sign |
| Tests for the dispersion parameter in Poisson distribution | pois.test poisdisp.test |
| Topological sort of a DAG | topological_sort |
| Transpose of a matrix | transpose |
| Uniformity tests for circular data | kuiper watson |
| Variance (and standard deviation) of a vector | Var |
| Vector allocation in a symmetric matrix | squareform |
| Weibull regression model | weib.reg |
| Yule's Y (coefficient of colligation) | yule |
