| cat.goftests |
Many one sample goodness of fit tests for categorical data |
| cauchy.mle |
MLE of continuous univariate distributions defined on the real line |
| checkAliases |
Check Namespace and Rd files |
| checkExamples |
Check Namespace and Rd files |
| checkNamespace |
Check Namespace and Rd files |
| checkTF |
Check Namespace and Rd files |
| checkUsage |
Check Namespace and Rd files |
| check_data |
Search for variables with zero range in a matrix |
| chi2Test |
G-square test of conditional indepdence |
| chi2tests |
Many G-square tests of indepedence |
| chi2Test_univariate |
Matrix with G-square tests of indepdence |
| chisq.mle |
MLE of continuous univariate distributions defined on the positive line |
| cholesky |
Cholesky decomposition of a square matrix |
| Choose |
Binomial coefficient and its logarithm |
| circlin.cor |
Circular-linear correlation |
| coeff |
Coefficient matrices. |
| col.coxpoisrat |
Cox confidence interval for the ratio of two Poisson variables |
| col.yule |
Column-wise Yule's Y (coefficient of colligation) |
| colAll |
Column and row-wise Any |
| colanovas |
Many Welch's F-tests |
| colAny |
Column and row-wise Any |
| colar1 |
Estimation of an AR(1) model |
| colaucs |
Many area under the curve values |
| colCountValues |
Row - Wise matrix/vector count the frequency of a value |
| colCumMaxs |
Colum-wise cumulative operations (sum, prod, min, max) |
| colCumMins |
Colum-wise cumulative operations (sum, prod, min, max) |
| colCumProds |
Colum-wise cumulative operations (sum, prod, min, max) |
| colCumSums |
Colum-wise cumulative operations (sum, prod, min, max) |
| colcvs |
Column and row wise coefficients of variation |
| coldiffs |
Column-wise differences |
| colexp2.mle |
Column-wise MLE of some univariate distributions |
| colexpmle |
Column-wise MLE of some univariate distributions |
| colFalse |
Column-wise true/false value of a matrix |
| colgammamle |
Column-wise MLE of some univariate distributions |
| colgeom.mle |
MLE for multivariate discrete data |
| colhameans |
Column and row-wise means of a matrix |
| colinvgauss.mle |
Column-wise MLE of some univariate distributions |
| colkurtosis |
Column-wise kurtosis and skewness coefficients |
| collaplace.mle |
Column-wise MLE of some univariate distributions |
| collindley.mle |
Column-wise MLE of some univariate distributions |
| colMads |
Column and row-wise mean absolute deviations |
| colmaxboltz.mle |
Column-wise MLE of some univariate distributions |
| colMaxs |
Column-wise minimum and maximum of a matrix |
| colmeans |
Column and row-wise means of a matrix |
| colmeans.data.frame |
Column and row-wise means of a matrix |
| colmeans.matrix |
Column and row-wise means of a matrix |
| colMedians |
Column and row-wise medians of a matrix or median of a vector. |
| colMins |
Column-wise minimum and maximum of a matrix |
| colMinsMaxs |
Column-wise minimum and maximum of a matrix |
| colnormal.mle |
Column-wise MLE of some univariate distributions |
| colnormlog.mle |
Column-wise MLE of some univariate distributions |
| colnth |
Column and row-wise nth smallest value of a matrix/vector |
| colOrder |
Column and row-wise Order - Sort Indices |
| colpareto.mle |
Column-wise MLE of some univariate distributions |
| colPmax |
Minima and maxima of two vectors/matrices and Column-row wise minima and maxima of two matrices |
| colPmin |
Minima and maxima of two vectors/matrices and Column-row wise minima and maxima of two matrices |
| colpois.tests |
Many tests for the dispersion parameter in Poisson distribution |
| colpoisdisp.tests |
Many tests for the dispersion parameter in Poisson distribution |
| colpoisson.anovas |
Many ANOVAS for count data with Poisson or quasi Poisson models |
| colpoisson.mle |
MLE for multivariate discrete data |
| colprods |
Column and row-wise products |
| colquasipoisson.anovas |
Many ANOVAS for count data with Poisson or quasi Poisson models |
| colrange |
Column and row-wise range of values of a matrix. |
| colRanks |
Column and row-wise ranks |
| colrayleigh.mle |
Column-wise MLE of some univariate distributions |
| colrint.regbx |
Many random intercepts LMMs for balanced data with a single identical covariate |
| colrow.value |
Check if any column or row is fill with values |
| colShuffle |
Column and row-wise Shuffle |
| colskewness |
Column-wise kurtosis and skewness coefficients |
| colSort |
Sorting of the columns-rows of a matrix |
| colsums |
Column and row-wise sums of a matrix |
| colTabulate |
Column and row-wise tabulate |
| colTrue |
Column-wise true/false value of a matrix |
| colTrueFalse |
Column-wise true/false value of a matrix |
| columns |
Get specific columns/rows fo a matrix |
| colvarcomps.mle |
Many moment and maximum likelihood estimations of variance components |
| colvarcomps.mom |
Many moment and maximum likelihood estimations of variance components |
| colVars |
Column and row-wise variances and standard deviations of a matrix |
| colVars.data.frame |
Column and row-wise variances and standard deviations of a matrix |
| colVars.matrix |
Column and row-wise variances and standard deviations of a matrix |
| colvm.mle |
Column-wise MLE of some univariate distributions |
| colwatsons |
Column-wise uniformity tests for circular data |
| colweibull.mle |
Column-wise MLE of some univariate distributions |
| comb_n |
All k possible combinations from n elements |
| cor.fbed |
FBED variable selection method using the correlation |
| cor.fsreg |
Correlation based forward regression. |
| cora |
Fast covariance and correlation matrix calculation |
| corpairs |
Correlation between pairs of variables |
| correls |
Correlation between a vector and a set of variables |
| count_value |
Row - Wise matrix/vector count the frequency of a value |
| cova |
Fast covariance and correlation matrix calculation |
| cox.poisrat |
Cox confidence interval for the ratio of two Poisson variables |
| cqtest |
Multi-sample tests for vectors |
| cqtests |
Many multi-sample tests |
| Crossprod |
Matrix multiplication, Cross and Tcross product. |
| ct.mle |
MLE of continuous univariate distributions defined on the real line |
| g2Test |
G-square test of conditional indepdence |
| g2tests |
Many G-square tests of indepedence |
| g2tests_perm |
Many G-square tests of indepedence |
| g2Test_perm |
G-square test of conditional indepdence |
| g2Test_univariate |
Matrix with G-square tests of indepdence |
| g2Test_univariate_perm |
Matrix with G-square tests of indepdence |
| gammacon |
Gamma regression with a log-link |
| gammamle |
MLE of continuous univariate distributions defined on the positive line |
| gammanb |
Naive Bayes classifiers |
| gammanb.pred |
Prediction with some naive Bayes classifiers |
| gammareg |
Gamma regression with a log-link |
| gammaregs |
Many simple regressions for positive valued data |
| gaussian.nb |
Naive Bayes classifiers |
| gaussiannb.pred |
Prediction with some naive Bayes classifiers |
| gchi2Test |
Chi-square and G-square tests of (unconditional) indepdence |
| geom.anova |
Analysis of variance with a count variable |
| geom.anovas |
Many analysis of variance tests with a discrete variable |
| geom.mle |
MLE of count data |
| geom.nb |
Naive Bayes classifiers |
| geom.regs |
Many simple geometric regressions. |
| geomnb.pred |
Prediction with some naive Bayes classifiers |
| ginis |
Many Gini coefficients |
| glm_logistic |
Logistic and Poisson regression models |
| glm_poisson |
Logistic and Poisson regression models |
| group |
Some summary statistics of a vector for each level of a grouping variable. |
| group.sum |
Some summary statistics of a vector for each level of a grouping variable. |
| groupcorrels |
Correlation between a vector and a set of variables |
| gumbel.mle |
MLE of continuous univariate distributions defined on the real line |
| laplace.mle |
MLE of continuous univariate distributions defined on the real line |
| Lbeta |
Natural logarithm of the beta function |
| Lchoose |
Binomial coefficient and its logarithm |
| length.Hash |
Hash object |
| Lgamma |
Natural logarithm of the gamma function and its derivatives. |
| lindley.mle |
MLE of continuous univariate distributions defined on the positive line |
| list.ftests |
Many F-tests with really huge matrices |
| lmfit |
Linear models for large scale data |
| Log |
Natural Logarithm each element of a matrix |
| logcauchy.mle |
MLE of continuous univariate distributions defined on the positive line |
| logistic.cat1 |
Logistic or Poisson regression with a single categorical predictor |
| logistic.mle |
MLE of continuous univariate distributions defined on the real line |
| logistic_only |
Many univariate simple binary logistic regressions |
| logitnorm.mle |
MLE of distributions defined in the (0, 1) interval |
| loglogistic.mle |
MLE of continuous univariate distributions defined on the positive line |
| lognorm.mle |
MLE of continuous univariate distributions defined on the positive line |
| logseries.mle |
MLE of count data |
| lomax.mle |
MLE of continuous univariate distributions defined on the positive line |
| lower_tri |
Lower and Upper triangular of a matrix |
| lower_tri.assign |
Lower and Upper triangular of a matrix |
| Mad |
Column and row-wise mean absolute deviations |
| mahala |
Mahalanobis distance |
| mat.mat |
Number of equal columns between two matrices |
| mat.mult |
Matrix multiplication, Cross and Tcross product. |
| Match |
Match |
| match.coefs |
Column-wise matching coefficients |
| matrnorm |
Generates random values from a normal and puts them in a matrix |
| maxboltz.mle |
MLE of continuous univariate distributions defined on the positive line |
| mcnemar |
Multi-sample tests for vectors |
| mcnemars |
Many 2 sample tests tests |
| med |
Column and row-wise medians of a matrix or median of a vector. |
| Median |
Column and row-wise medians of a matrix or median of a vector. |
| mediandir |
Fast calculation of the spherical and hyperspherical median |
| min_max |
Minimum and maximum of a vector |
| multinom.mle |
MLE for multivariate discrete data |
| multinom.nb |
Naive Bayes classifiers |
| multinom.reg |
Multinomial regression |
| multinom.regs |
Many simple multinomial regressions. |
| multinomnb.pred |
Prediction with some naive Bayes classifiers |
| multivmf.mle |
MLE of (hyper-)spherical distributions |
| mv.eeltest1 |
Exponential empirical likelihood for a one sample mean vector hypothesis testing |
| mv.eeltest2 |
Exponential empirical likelihood hypothesis testing for two mean vectors |
| mvbetas |
Many multivariate simple linear regressions coefficients |
| mvkurtosis |
Multivariate kurtosis |
| mvlnorm.mle |
MLE of the multivariate (log-) normal distribution |
| mvnorm.mle |
MLE of the multivariate (log-) normal distribution |
| mvt.mle |
MLE of the multivariate t distribution |
| pareto.mle |
MLE of continuous univariate distributions defined on the positive line |
| pc.skel |
The skeleton of a Bayesian network produced by the PC algorithm |
| percent.ttest |
Hypothesis test for two means of percentages |
| percent.ttests |
Many hypothesis tests for two means of percentages |
| permcor |
Permutation based p-value for the Pearson correlation coefficient |
| permutation |
Permutation |
| permutation.next |
Permutation |
| permutation.prev |
Permutation |
| Pmax |
Minima and maxima of two vectors/matrices and Column-row wise minima and maxima of two matrices |
| Pmin |
Minima and maxima of two vectors/matrices and Column-row wise minima and maxima of two matrices |
| Pmin_Pmax |
Minima and maxima of two vectors/matrices and Column-row wise minima and maxima of two matrices |
| pois.test |
Tests for the dispersion parameter in Poisson distribution |
| poisdisp.test |
Tests for the dispersion parameter in Poisson distribution |
| poisson.anova |
Analysis of variance with a count variable |
| poisson.anovas |
Many analysis of variance tests with a discrete variable |
| poisson.cat1 |
Logistic or Poisson regression with a single categorical predictor |
| poisson.mle |
MLE of count data |
| poisson.nb |
Naive Bayes classifiers |
| poissonnb.pred |
Prediction with some naive Bayes classifiers |
| poisson_only |
Many univariate simple binary logistic regressions |
| poly.cor |
Polyserial correlation |
| pooled.cov |
Pooled covariance matrix |
| positive |
Apply method to Positive and Negative number |
| positive.negative |
Apply method to Positive and Negative number |
| print.Hash |
Hash object |
| print.iterator |
Iterator |
| print.ufactor |
Fast and general represantation of a factor variable |
| prop.reg |
Quasi binomial regression for proportions |
| prop.regs |
Quasi binomial regression for proportions |
| proptest |
Many one sample tests |
| proptests |
Many 2 sample proportions tests |
| racg |
Angular central Gaussian random values simulation |
| Rank |
Column and row-wise ranks |
| rayleigh.mle |
MLE of continuous univariate distributions defined on the positive line |
| rbing |
Simulating from a Bingham distribution |
| rbingham |
Simulation of random values from a Bingham distribution with any symmetric matrix |
| read.directory |
Reading the files of a directory |
| read.examples |
Reading the files of a directory |
| regression |
Many univariate simple linear regressions |
| rel.risk |
Odds ratio and relative risk |
| RemoveFromNamespace |
Insert/remove function names in/from the NAMESPACE file |
| rep_col |
Replicate columns/rows |
| rep_row |
Replicate columns/rows |
| rint.mle |
Moment and maximum likelihood estimation of variance components |
| rint.reg |
Random intercepts linear mixed models |
| rint.regbx |
Random intercepts linear mixed models |
| rint.regs |
Many simple linear mixed model regressions |
| rm.anova |
Repeated measures anova |
| rm.anovas |
Many regression based tests for single sample repeated measures |
| rm.lines |
Many regression based tests for single sample repeated measures |
| rmdp |
High dimensional MCD based detection of outliers |
| rmvlaplace |
Multivariate Laplace random values simulation |
| rmvnorm |
Multivariate normal and t random values simulation |
| rmvt |
Multivariate normal and t random values simulation |
| Rnorm |
Simulation of random values from a normal distribution |
| Round |
Round each element of a matrix/vector |
| rowAll |
Column and row-wise Any |
| rowAny |
Column and row-wise Any |
| rowCountValues |
Row - Wise matrix/vector count the frequency of a value |
| rowcvs |
Column and row wise coefficients of variation |
| rowFalse |
Row-wise true value of a matrix |
| rowhameans |
Column and row-wise means of a matrix |
| rowMads |
Column and row-wise mean absolute deviations |
| rowMaxs |
Row-wise minimum and maximum of a matrix. |
| rowmeans |
Column and row-wise means of a matrix |
| rowMedians |
Column and row-wise medians of a matrix or median of a vector. |
| rowMins |
Row-wise minimum and maximum of a matrix. |
| rowMinsMaxs |
Row-wise minimum and maximum of a matrix. |
| rownth |
Column and row-wise nth smallest value of a matrix/vector |
| rowOrder |
Column and row-wise Order - Sort Indices |
| rowprods |
Column and row-wise products |
| rowrange |
Column and row-wise range of values of a matrix. |
| rowRanks |
Column and row-wise ranks |
| rows |
Get specific columns/rows fo a matrix |
| rowShuffle |
Column and row-wise Shuffle |
| rowSort |
Sorting of the columns-rows of a matrix |
| rowsums |
Column and row-wise sums of a matrix |
| rowTabulate |
Column and row-wise tabulate |
| rowTrue |
Row-wise true value of a matrix |
| rowTrueFalse |
Row-wise true value of a matrix |
| rowVars |
Column and row-wise variances and standard deviations of a matrix |
| rvmf |
Random values simulation from a von Mises-Fisher distribution |
| rvonmises |
Random values simulation from a von Mises distribution |