*Rfast2*

New

Function What’s new! jbtests Many Jarque–Bera normality tests lm.nonparboot Non-parametric bootstrap for linear models normal.etest Energy based normality test batch.logistic Logistic regression for large scale data colhalfcauchy.mle Column-wise MLE for the half Cauchy distribution colcenspois.mle Column-wise MLE for the censored Poisson distribution colcensweibull.mle Column-wise MLE for the censored Weibull distribution el.cor.test Empirical likelihood test for the correlation coefficient eel.cor.test Exponential empirical likelihood test for the correlation coefficient jbtest Jarque–Bera normality test

Improved(

)by speed, correctness or options

Function What’s new! halfcauchy.mle Time improvement censpois.mle Time improvement censweibull.mle Time improvement

LinkingTo(

)by speed, correctness or options

Function/Structure What’s new!

Improved(

)by speed, correctness or options

Function What’s new! TrimMean Add option for parallelism. Supported only where C++ execution policy is supported. Quantile Add option for parallelism. Supported only where C++ execution policy is supported.

LinkingTo(

)by speed, correctness or options

Function/Structure What’s new! Quantile Exported for linking rowQuantile Exported for linking colQuantile Exported for linking TrimMean Exported for linking rowTrimMean Exported for linking colTrimMean Exported for linking colTrimMean Exported for linking

Comments

- All the exported functions for linking to mechanism are in namespace
`Rfast`

.- We have added the header file
`parallel.h`

which automatically includes the new parallelism policy rules of C++17. If not supported by your system, non-parallel algorithms are automatically used.

New

Function What’s new! covrob.lm Linear regression with robust covariance matrix

New

Function What’s new! Runif Like R’s runif but faster. Sample Like R’s Sample but faster. Sample.int Like R’s Sample.int but faster. colaccs Column-wise accuracies colsens Column-wise sensitivities colspecs Column-wise specificities colprecs Column-wise precisions colfscores Column-wise F-scores colfbscores Column-wise F-beta-scores colfmis Column-wise Fowlkes–Mallows index colfmses Column-wise MSEs colmaes Column-wise MAEs colpkl Column-wise Kullback-Leibler divergence for percentages colukl Column-wise Kullback-Leibler divergence for non-negative or non-negative values pinar1 Poisson INAR(1) model estimation colpinar1 Column-wise Poisson INAR(1) model estimation

Improved(

)by speed, correctness or options

Function What’s new! Quantile, rowQuantile Optimize algorithm colQuantile Optimize algorithm and new method for data.frames colTrimMean Optimize algorithm and new method for data.frames

New

Function What’s new! mmhc.skel Skeleton of MMHC Bayesian network learning algorithm fedhc.skel Skeleton of FEDHC Bayesian network learning algorithm fe.lmfit Fixed effects linear regression for panel data

New

Function What’s new! gammareg Gamma regression gammaregs Many gamma regressions cor_test Hypothesis testing for the correlation coefficient cor_test Hypothesis testing for the correlation coefficient hcf.circaov ANOVA for circular data het.circaov ANOVA for circular data lr.circaov ANOVA for circular data multivm.mle Fitting many von Mises distributions multispml.mle Fitting many von SPML distributions depth.mahala Mahalanobis depth perm.ttest2 Permutation based 2 sample t-test lm.parboot Parametric bootstrap for linear models weibull.nb Weibull Naive Bayes (NB) classifier weibullnb.pred Prediction using Weibull NB classifier normlog.nb Gaussian(log-link) NB classifier normlognb.pred Prediction using Gaussian(log-link) NB classifier laplace.nb Laplace NB classifier laplacenb.pred Prediction using Laplace NB classifier vm.nb von Mises NB classifier vmnb.pred Prediction using von Mises NB classifier spml.nb SPML NB classifier spml.pred Prediction using SPML NB classifier

Improved(

)by speed, correctness or options

Function What’s new! bic.regs Addition SPML and Weibull regression pc.sel Time improvement welch.tests Time improevement

New

Function What’s new! cls Constrained least squares regression cluster.lm Linear regression with clustered data colborel.mle Column-wise MLE of the Borel distribution collogitnorm.mle Column-wise MLE of the logistic normal distribution collognorm.mle Column-wise MLE of the log-normal distribution cospml.mle Column-wise MLE of the SPML distribution empirical.entropy Empirical entropy estimation with continuous data fbed.reg FBED variable selection algorithm gumbel.reg Gumbel regression moranI Moran’s I measure of spatial autocorrelation multinom.reg Multinomial regression negbin.reg Negative binomial regression pca Principal component analysis refmeta Random effects meta-analysis estimation simplex.mle MLE of the simplex distribution weib.regs Many simple weibull regressions ztp.reg zero truncated Poisson regression mmpc2 MMPC variable selection algorithm is.skew.symmetric Checking if the given matrix is skew-symmetric.

Improved(

)by speed, correctness or options

Function What’s new! benchmark fix a bug in printing names.

New

Function What’s new! gee.reg Gereneralised estimating equations Gaussian regression halfcauchy.mle MLE of the half Cauchy distribution kumar.mle MLE of the Kumaraswamy distribution powerlaw.mle MLE of the power law distribution reg.mle.lda Regularised maximum likleihood linear discriminant analysis walter.ci Confidence interval for the relative risk using Walter’s method welch.tests Many Welch t-tests

New

Function What’s new! add.term Add many single terms to a model. bic.regs BIC of many univariate regressions. censpois.mle MLE of the left censored Poisson distribution. cesweibull.mle MLE of the censored Weibull distribution. circ.cor1 Circurlar correlations between two circular variables. circ.cors1 Circurlar correlations between a circular and many circular variables. colmeansvars Column-wise means and variances of a matrix. covar Covariance betweeen a vector and a matrix. diffic Difficulty of items (psychometric theory). discrim Discrimination of items (psychometric theory). gammapois.mle MLE of the gamma-Poisson distribution. km Kaplan-Meier estimate of a survival function. logiquant.regs Many simple quantile regressions using logistic regressions. mle.lda Maximum likelihood linear discriminant analysis. pc.sel Variable selection using the PC-simple algorithm. pooled.colVars Column-wise pooled variances across groups. purka.mle MLE of the Purkayastha distribution. sp.logiregs Many approximate simple logistic regressionss. trunccauchy.mle MLE of the truncated Cauchy distribution. truncexpmle MLE of the truncated exponential distribution. wald.poisrat Wald confidence interval for the ratio of two Poisson variables. col.waldpoisrat Column-wise Wald confidence interval for the ratio of two Poisson variables. welch.tests Many Welch tests. zigamma.mle MLE of the zero inflated Gamma distribution. ziweibull.mle MLE of the zero inflated Weibull distribution. zil.mle MLE of the zero inflated logistic normal distribution. Intersect Intersect as R’s. is.lower.tri Check if a matrix is lower triangular. is.upper.tri Check if a matrix is upper triangular. lud Split a matrix to a lower,upper matrix and diagonal vector. Merge Merge 2 sorted vectors to a sorted vector. benchmark Measure code’s execution time. colGroup Apply Rfast’s gorup function to each column with some restrictions. Quantile Quantile(s) of a vector. colQuantile Column-wise quantile(s) of a matrix. rowQuantile Row-wise quantile(s) of a matrix. trim.mean Trimmed mean of a vector. colTrimMean Column-wise trimmed mean of a matrix. rowTrimMean Row-wise trimmed mean of a matrix.