| batch.logistic | Logistic regression for large scale data | 
| benchmark | Benchmark - Measure time | 
| bernoulli.nb | Naive Bayes classifier for binary Bernoulli data | 
| bernoullinb.pred | Prediction with naive Bayes classifier for binary (Bernoulli) data | 
| beta.nb | Naive Bayes classifiers | 
| betanb.pred | Prediction with some naive Bayes classifiers | 
| bic.regs | BIC of many simple univariate regressions. | 
| big.knn | The k-NN algorithm for really lage scale data | 
| bigknn.cv | Cross-validation for the k-NN algorithm for really lage scale data | 
| binom.reg | Binomial regression | 
| boot.hotel2 | Bootstrap James and Hotelling test for 2 independent sample mean vectors | 
| boot.james | Bootstrap James and Hotelling test for 2 independent sample mean vectors | 
| boot.student2 | Bootstrap Student's t-test for 2 independent samples | 
| boot.ttest1 | One sample bootstrap t-test for a vector | 
| cauchy.nb | Naive Bayes classifiers | 
| cauchy0.mle | MLE of the Cauchy and generalised normal distributions with zero location | 
| cauchynb.pred | Prediction with some naive Bayes classifiers | 
| cbern.mle | MLE of distributions defined for proportions | 
| censpois.mle | MLE of the left censored Poisson distribution | 
| censweib.reg | Censored Weibull regression model | 
| censweibull.mle | MLE of the censored Weibull distribution | 
| circ.cor1 | Circurlar correlations between two circular variables | 
| circ.cors1 | Circurlar correlations between two circular variables | 
| cls | Constrained least squares | 
| cluster.lm | Linear regression with clustered data | 
| col.waldpoisrat | Wald confidence interval for the ratio of two Poisson variables | 
| colaccs | Many binary classification metrics | 
| colbeta.mle | Column-wise MLE of some univariate distributions | 
| colborel.mle | Column-wise MLE of some univariate distributions | 
| colcauchy.mle | Column-wise MLE of some univariate distributions | 
| colcenspois.mle | Column-wise MLE of some univariate distributions | 
| colcensweibull.mle | Column-wise MLE of some univariate distributions | 
| colfbscores | Many binary classification metrics | 
| colfmis | Many binary classification metrics | 
| colfscores | Many binary classification metrics | 
| colGroup | Column-wise summary statistics with grouping variables | 
| colhalfcauchy.mle | Column-wise MLE of some univariate distributions | 
| colhalfnorm.mle | Column-wise MLE of some univariate distributions | 
| coljack.means | Column and row-wise jackknife sample means | 
| collogitnorm.mle | Column-wise MLE of some univariate distributions | 
| collognorm.mle | Column-wise MLE of some univariate distributions | 
| colmaes | any metrics for a continuous response variable | 
| colmeansvars | Column-wise means and variances of a matrix | 
| colmses | any metrics for a continuous response variable | 
| colordinal.mle | Column-wise MLE of some univariate distributions | 
| colpinar1 | Conditional least-squares estimate for Poisson INAR(1) models | 
| colpkl | any metrics for a continuous response variable | 
| colpowerlaw.mle | Column-wise MLE of some univariate distributions | 
| colprecs | Many binary classification metrics | 
| colQuantile | Sample quantiles and col/row wise quantiles | 
| colQuantile.data.frame | Sample quantiles and col/row wise quantiles | 
| colQuantile.matrix | Sample quantiles and col/row wise quantiles | 
| colsens | Many binary classification metrics | 
| colsp.mle | Column-wise MLE of some univariate distributions | 
| colspecs | Many binary classification metrics | 
| colspml.mle | Column-wise MLE of the angular Gaussian distribution | 
| colTrimMean | Trimmed mean | 
| colTrimMean.data.frame | Trimmed mean | 
| colTrimMean.matrix | Trimmed mean | 
| colukl | any metrics for a continuous response variable | 
| colunitweibull.mle | Column-wise MLE of some univariate distributions | 
| colwlsmeta | Column-wise weighted least squares meta analysis | 
| cor_test | Correlation significance testing using Fisher's z-transformation | 
| covar | Covariance between a variable and a set of variables | 
| covdist | Distance between two covariance matrices | 
| covequal | Hypothesis test for equality of a covariance matrix | 
| covlikel | Hypothesis tests for equality of multiple covariance matrices | 
| covmtest | Hypothesis tests for equality of multiple covariance matrices | 
| covrob.lm | Linear model with sandwich robust covariance estimator | 
| laplace.nb | Naive Bayes classifiers | 
| laplacenb.pred | Prediction with some naive Bayes classifiers | 
| leverage | Diagonal values of the Hat matrix | 
| lm.bsreg | backward selection with the F test or the partial correlation coefficient | 
| lm.drop1 | Single terms deletion hypothesis testing in a linear regression model | 
| lm.nonparboot | Parametric and non-parametric bootstrap for linear regression model | 
| lm.parboot | Parametric and non-parametric bootstrap for linear regression model | 
| logiquant.regs | Many simple quantile regressions using logistic regressions. | 
| logitnorm.nb | Naive Bayes classifiers | 
| logitnormnb.pred | Prediction with some naive Bayes classifiers | 
| lr.circaov | Analysis of variance for circular data | 
| lud | Split the matrix in lower, upper triangular and diagonal | 
| mci | Monte Carlo Integration with a normal distribution | 
| Merge | Merge 2 sorted vectors in 1 sorted vector | 
| mle.lda | Maximum likelihood linear discriminant analysis | 
| mmhc.skel | The skeleton of a Bayesian network learned with the MMHC algorithm | 
| mmpc | Max-Min Parents and Children variable selection algorithm for continuous responses | 
| mmpc2 | Max-Min Parents and Children variable selection algorithm for non continuous responses | 
| moranI | Moran's I measure of spatial autocorrelation | 
| multinom.reg | Multinomial regression | 
| multinomreg.cv | Cross-validation for the multinomial regression | 
| multispml.mle | MLE of some circular distributions with multiple samples | 
| multivm.mle | MLE of some circular distributions with multiple samples | 
| mv.score.betaregs | Many score based regressions with muliple response variables and a single predictor variable | 
| mv.score.expregs | Many score based regressions with muliple response variables and a single predictor variable | 
| mv.score.gammaregs | Many score based regressions with muliple response variables and a single predictor variable | 
| mv.score.glms | Many score based regressions with muliple response variables and a single predictor variable | 
| mv.score.invgaussregs | Many score based regressions with muliple response variables and a single predictor variable | 
| mv.score.weibregs | Many score based regressions with muliple response variables and a single predictor variable | 
| pc.sel | Variable selection using the PC-simple algorithm | 
| pca | Principal component analysis | 
| pcr | Principal components regression | 
| perm.ttest2 | Permutation t-test for 2 independent samples | 
| pinar1 | Conditional least-squares estimate for Poisson INAR(1) models | 
| pooled.colVars | Column-wise pooled variances across groups | 
| powerlaw.mle | MLE of continuous univariate distributions defined on the positive line | 
| print.benchmark | Benchmark - Measure time | 
| prophelling.reg | Hellinger distance based univariate regression for proportions | 
| propols.reg | Non linear least squares regression for percentages or proportions | 
| purka.mle | MLE of the Purkayastha distribution | 
| rbeta1 | Random values generation from a Be(a, 1) distribution | 
| refmeta | Random effects and weighted least squares meta analysis | 
| reg.mle.lda | Regularised maximum likelihood linear discriminant analysis | 
| regmlelda.cv | Cross-validation for the regularised maximum likelihood linear discriminant analysis | 
| riag | Angular Gaussian random values simulation | 
| rm.hotel | Repeated measures ANOVA (univariate data) using Hotelling's T^2 test | 
| rowjack.means | Column and row-wise jackknife sample means | 
| rowQuantile | Sample quantiles and col/row wise quantiles | 
| rowTrimMean | Trimmed mean | 
| Runif | Random values simulation from the uniform distribution |