| Really fast R functions | Rfast2-package |
| Add many single terms to a model | add.term |
| Angular Gaussian random values simulation | riag |
| Analysis of variance for circular data | embed.circaov hcf.circaov het.circaov lr.circaov |
| backward selection with the F test or the partial correlation coefficient | lm.bsreg |
| Benchmark - Measure time | benchmark print.benchmark |
| Bessel functions | bessel |
| BIC of many simple univariate regressions | bic.regs |
| Binomial regression | binom.reg |
| Bootstrap James and Hotelling test for 2 independent sample mean vectors | boot.hotel2 boot.james |
| Bootstrap Student's t-test for 2 independent samples | boot.student2 |
| Censored Weibull regression model | censweib.reg |
| Check if a matrix is Lower or Upper triangular | is.lower.tri is.upper.tri |
| Check whether a square matrix is skew-symmetric | is.skew.symmetric |
| Circurlar correlations between two circular variables | circ.cor1 circ.cors1 |
| Cluster robust wild bootstrap for linear models | wild.boot |
| Column and row-wise jackknife sample means | coljack.means rowjack.means |
| Column-wise means and variances of a matrix | colmeansvars |
| Column-wise MLE of some univariate distributions | colbeta.mle colborel.mle colcauchy.mle colcenspois.mle colcensweibull.mle colhalfcauchy.mle colhalfnorm.mle collogitnorm.mle collognorm.mle colordinal.mle colpowerlaw.mle colsp.mle colunitweibull.mle |
| Column-wise MLE of the angular Gaussian distribution | colspml.mle |
| Column-wise pooled variances across groups | pooled.colVars |
| Column-wise summary statistics with grouping variables | colGroup |
| Column-wise weighted least squares meta analysis | colwlsmeta |
| Conditional least-squares estimate for Poisson INAR(1) models | colpinar1 pinar1 |
| Constrained least squares | cls |
| Contour plots of some bivariate distributions | den.contours |
| Correlation significance testing using Fisher's z-transformation | cor_test |
| Covariance between a variable and a set of variables | covar |
| Cross-validation for the k-NN algorithm for really lage scale data | bigknn.cv |
| Cross-validation for the multinomial regression | multinomreg.cv |
| Cross-validation for the naive Bayes classifiers | nb.cv |
| Cross-validation for the regularised maximum likelihood linear discriminant analysis | regmlelda.cv |
| Diagonal values of the Hat matrix | leverage |
| Distance between two covariance matrices | covdist |
| Distance correlation matrix | dcora |
| Empirical and exponential empirical likelihood test for a correlation coefficient | eel.cor.test el.cor.test |
| Empirical entropy | empirical.entropy |
| Energy based normality test | normal.etest |
| Energy test of equal univariate distributions | eqdist.etest |
| Fisher's linear discriminant analysis | fisher.da |
| Fixed effects regression | fe.lmfit |
| Fixed intercepts Poisson regression | fipois.reg |
| Forward Backward Early Dropping selection regression | fbed.reg |
| Fractional polynomial regression with one independent variable | fp |
| Frechet mean for compositional data with k-nearest neighbours | frechet.nn |
| Gamma regression with a log-link | gammareg |
| GEE Gaussian regression | gee.reg |
| Gumbel regression | gumbel.reg |
| Hellinger distance based regression for count data | hellinger.countreg |
| Hellinger distance based univariate regression for proportions | prophelling.reg |
| Heteroscedastic linear models for large scale data | het.lmfit |
| Hurdle-Poisson regression | hp.reg |
| Hypothesis test for equality of a covariance matrix | covequal |
| Hypothesis tests for equality of multiple covariance matrices | covlikel covmtest |
| Intersect Operation | Intersect |
| Item difficulty and discrimination | diffic discrim |
| Jackknife sample mean | jack.mean |
| Kaplan-Meier estimate of a survival function | km |
| Linear model with sandwich robust covariance estimator | covrob.lm |
| Linear regression with clustered data | cluster.lm |
| Logistic regression for large scale data | batch.logistic |
| Mahalanobis depth | depth.mahala |
| Many 2 sample student's t-tests | stud.ttests |
| Many approximate simple logistic regressions | sp.logiregs |
| Many binary classification metrics | colaccs colfbscores colfmis colfscores colprecs colsens colspecs |
| Many Gamma regressions | gammaregs |
| Many Jarque-Bera normality tests | jbtest jbtests |
| any metrics for a continuous response variable | colmaes colmses colpkl colukl |
| Many score based regressions with muliple response variables and a single predictor variable | mv.score.betaregs mv.score.expregs mv.score.gammaregs mv.score.glms mv.score.invgaussregs mv.score.weibregs |
| Many score based zero inflated Poisson regressions | score.zipregs |
| Many simple quantile regressions using logistic regressions | logiquant.regs |
| Many simple Weibull regressions | weib.regs |
| Many Welch tests | welch.tests |
| Max-Min Parents and Children variable selection algorithm for continuous responses | mmpc |
| Max-Min Parents and Children variable selection algorithm for non continuous responses | mmpc2 |
| Maximum likelihood linear discriminant analysis | mle.lda |
| Merge 2 sorted vectors in 1 sorted vector | Merge |
| MLE of continuous univariate distributions defined on the positive line | halfcauchy.mle powerlaw.mle |
| MLE of distributions defined for proportions | cbern.mle kumar.mle simplex.mle sp.mle unitweibull.mle zil.mle |
| MLE of some circular distributions with multiple samples | multispml.mle multivm.mle |
| MLE of some truncated distributions | trunccauchy.mle truncexpmle |
| MLE of the Cauchy and generalised normal distributions with zero location | cauchy0.mle gnormal0.mle |
| MLE of the censored Weibull distribution | censweibull.mle |
| MLE of the gamma-Poisson distribution | gammapois.mle |
| MLE of the left censored Poisson distribution | censpois.mle |
| MLE of the Purkayastha distribution | purka.mle |
| MLE of the zero inflated Gamma and Weibull distributions | zigamma.mle ziweibull.mle |
| Monte Carlo Integration with a normal distribution | mci |
| Moran's I measure of spatial autocorrelation | moranI |
| Multinomial regression | multinom.reg |
| Naive Bayes classifier for binary Bernoulli data | bernoulli.nb |
| Naive Bayes classifiers | beta.nb cauchy.nb laplace.nb logitnorm.nb normlog.nb weibull.nb |
| Naive Bayes classifiers for directional data | spml.nb vm.nb |
| Negative binomial regression | negbin.reg negbin.regs |
| Non linear least squares regression for percentages or proportions | propols.reg |
| One sample bootstrap permutation t-test for a vector | boot.ttest1 perm.ttest1 |
| Orthogonal matching variable selection | omp2 |
| Parametric and non-parametric bootstrap for linear regression model | lm.boot lm.nonparboot lm.parboot |
| Permutation t-test for one or two independent samples | perm.ttest perm.ttest2 |
| Prediction with naive Bayes classifier for binary (Bernoulli) data | bernoullinb.pred |
| Prediction with some naive Bayes classifiers | betanb.pred cauchynb.pred laplacenb.pred logitnormnb.pred normlognb.pred weibullnb.pred |
| Prediction with some naive Bayes classifiers for circular data | spmlnb.pred vmnb.pred |
| Principal component analysis | pca |
| Principal components regression | pcr |
| Random effects and weighted least squares meta analysis | refmeta wlsmeta |
| Random integer values simulation | Sample Sample.int |
| Random values generation from a Be(a, 1) distribution | rbeta1 |
| Random values simulation from various distributions | Runif |
| Regularised maximum likelihood linear discriminant analysis | reg.mle.lda |
| Repeated measures ANOVA (univariate data) using Hotelling's T^2 test | rm.hotel |
| Sample quantiles and col/row wise quantiles | colQuantile colQuantile.data.frame colQuantile.matrix Quantile rowQuantile |
| Scaled logistic regression | sclr |
| Score test for overdispersion in Poisson regression | overdispreg.test |
| Silhouette function | silhouette |
| Single terms deletion hypothesis testing in a linear regression model | lm.drop1 |
| The skeleton of a Bayesian network produced by the FEDHC algorithm | fedhc.skel |
| The skeleton of a Bayesian network learned with the MMHC algorithm | mmhc.skel |
| Split the matrix in lower, upper triangular and diagonal | lud |
| The k-NN algorithm for really lage scale data | big.knn |
| Tobit regression | tobit.reg |
| Trimmed mean | colTrimMean colTrimMean.data.frame colTrimMean.matrix rowTrimMean trim.mean |
| Univariate and multivariate kernel density estimation | kernel |
| Variable selection using the PC-simple algorithm | pc.sel |
| Wald confidence interval for the ratio of two Poisson variables | col.waldpoisrat wald.poisrat |
| Walter's confidence interval for the ratio of two binomial variables (and the relative risk) | walter.ci |
| Zero inflated Gamma regression | zigamma.reg |
| Zero truncated Poisson regression | ztp.reg |
