# A Collection of Efficient and Extremely Fast R Functions II

## Documentation for package ‘Rfast2’ version 0.1.5.1

- DESCRIPTION file.
- Package NEWS.

## Help Pages

A B C D E F G H I J K L M N O P Q R S T U V W Z

Rfast2-package | Really fast R functions

## -- A --

add.term | Add many single terms to a model

## -- B --

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

## -- C --

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
colfbscores | Many binary classification metrics
colfmis | Many binary classification metrics
colfscores | Many binary classification metrics
colGroup | Column-wise summary statistics with grouping variables
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
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
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 matrix 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

## -- D --

dcora | Distance correlation matrix
den.contours | Contour plots of some bivariate distributions
depth.mahala | Mahalanobis depth
diffic | Item difficulty and discrimination
discrim | Item difficulty and discrimination

## -- E --

embed.circaov | Analysis of variance for circular data
empirical.entropy | Empirical entropy

## -- F --

fbed.reg | Forward Backward Early Dropping selection regression
fe.lmfit | Fixed effects regression
fedhc.skel | The skeleton of a Bayesian network produced by the FEDHC algorithm
fipois.reg | Fixed intercepts Poisson regression
fisher.da | Fisher's linear discriminant analysis
fp | Fractional polynomial regression with one independent variable.

## -- G --

gammapois.mle | MLE of the gamma-Poisson distribution
gammareg | Gamma regression with a log-link
gammaregs | Many Gamma regressions
gee.reg | GEE Gaussian regression
gnormal0.mle | MLE of the Cauchy and generalised normal distributions with zero location
gumbel.reg | Gumbel regression

## -- H --

halfcauchy.mle | MLE of continuous univariate distributions defined on the positive line
hcf.circaov | Analysis of variance for circular data
hellinger.countreg | Hellinger distance based regression for count data
het.circaov | Analysis of variance for circular data
het.lmfit | Heteroscedastic linear models for large scale data
hp.reg | Hurdle-Poisson regression

## -- I --

Intersect | Intersect Operation
is.lower.tri | Check if a matrix is Lower or Upper triangular
is.skew.symmetric | Check whether a square matrix is skew-symmetric
is.upper.tri | Check if a matrix is Lower or Upper triangular

## -- J --

jack.mean | Jackknife sample mean

## -- K --

km | Kaplan-Meier estimate of a survival function
kumar.mle | MLE of distributions defined for proportions

## -- L --

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.parboot | 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

## -- M --

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

## -- N --

nb.cv | Cross-validation for the naive Bayes classifiers
negbin.reg | Negative binomial regression
negbin.regs | Many negative binomial regressions
normlog.nb | Naive Bayes classifiers
normlognb.pred | Prediction with some naive Bayes classifiers

## -- O --

omp2 | Orthogonal matching variable selection
overdispreg.test | Score test for overdispersion in Poisson regression

## -- P --

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

## -- Q --

Quantile | Sample quantiles and col/row wise quantiles

## -- R --

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

## -- S --

Sample | Random integer values simulation
Sample.int | Random integer values simulation
sclr | Scaled logistic regression
score.zipregs | Many score based zero inflated Poisson regressions
simplex.mle | MLE of distributions defined for proportions
sp.logiregs | Many approximate simple logistic regressions.
sp.mle | MLE of distributions defined for proportions
spml.nb | Naive Bayes classifiers for directional data
spmlnb.pred | Prediction with some naive Bayes classifiers for circular data
stud.ttests | Many 2 sample student's t-tests

## -- T --

tobit.reg | Tobit regression
trim.mean | Trimmed mean
trunccauchy.mle | MLE of some truncated distributions
truncexpmle | MLE of some truncated distributions

## -- U --

unitweibull.mle | MLE of distributions defined for proportions

## -- V --

vm.nb | Naive Bayes classifiers for directional data
vmnb.pred | Prediction with some naive Bayes classifiers for circular data

## -- W --

wald.poisrat | Wald confidence interval for the ratio of two Poisson variables
walter.ci | Walter's confidence interval for the ratio of two binomial variables (and the relative risk)
weib.regs | Many simple Weibull regressions.
weibull.nb | Naive Bayes classifiers
weibullnb.pred | Prediction with some naive Bayes classifiers
welch.tests | Many Welch tests.
wild.boot | Cluster robust wild bootstrap for linear models
wlsmeta | Random effects and weighted least squares meta analysis

## -- Z --

zigamma.mle | MLE of the zero inflated Gamma and Weibull distributions
zigamma.reg | Zero inflated Gamma regression
zil.mle | MLE of distributions defined for proportions
ziweibull.mle | MLE of the zero inflated Gamma and Weibull distributions
ztp.reg | Zero truncated Poisson regression