| 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 |
| bessel |
Bessel functions |
| 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 permutation 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.boot |
Parametric and non-parametric bootstrap for linear regression model |
| 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.ttest |
Permutation t-test for one or two independent samples |
| perm.ttest1 |
One sample bootstrap permutation t-test for a vector |
| perm.ttest2 |
Permutation t-test for one or two 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 various distributions |