Package index • Hmisc

All functions

Cs() .q(): Character strings from unquoted names
Ecdf(): Empirical Cumulative Distribution Plot
Fdebug(): Debug Printing Function Generator
GiniMd(): Gini's Mean Difference
Lag(): Lag a Numeric, Character, or Factor Vector
Merge(): Merge Multiple Data Frames or Data Tables
confbar() getLatestSource() grType() prType() htmlSpecialType() inverseFunction() james.stein() keepHattrib() km.quick() latexBuild() lm.fit.qr.bare() matxv() nomiss() outerText() plotlyParm plotp() rendHTML() restoreHattrib() sepUnitsTrans() strgraphwrap() tobase64image() trap.rule() trellis.strip.blank() unPaste() whichClosest() whichClosePW() whichClosek() xless(): Miscellaneous Functions
HmiscOverview Hmisc.Overview: Overview of Hmisc Library
R2Measures(): R2Measures
Save() Load(): Faciliate Use of save and load to Remote Directories
abs.error.pred() print(<abs.error.pred>): Indexes of Absolute Prediction Error for Linear Models
addMarginal(): Add Marginal Observations
addggLayers(): addggLayers
all.is.numeric(): Check if All Elements in Character Vector are Numeric
approxExtrap(): Linear Extrapolation
areg() print(<areg>) plot(<areg>) predict(<areg>): Additive Regression with Optimal Transformations on Both Sides using Canonical Variates
aregImpute() print(<aregImpute>) plot(<aregImpute>) reformM(): Multiple Imputation using Additive Regression, Bootstrapping, and Predictive Mean Matching
biVar() print(<biVar>) plot(<biVar>) spearman2() spearman() spearman.test() chiSquare(): Bivariate Summaries Computed Separately by a Series of Predictors
binconf(): Confidence Intervals for Binomial Probabilities
bootkm(): Bootstrap Kaplan-Meier Estimates
bpower() bsamsize() ballocation() bpower.sim(): Power and Sample Size for Two-Sample Binomial Test
bpplot(): Box-percentile plots
bystats() print(<bystats>) latex(<bystats>) bystats2() print(<bystats2>) latex(<bystats2>): Statistics by Categories
capitalize(): capitalize the first letter of a string
ciapower(): Power of Interaction Test for Exponential Survival
cnvrt.coords(): Convert between the 5 different coordinate sytems on a graphical device
combine.levels(): combine.levels
combplotp(): Combination Plot
completer(): completer
consolidate() `consolidate<-`(): Element Merging
contents() print(<contents.data.frame>) html(<contents.data.frame>) print(<contents.list>): Metadata for a Data Frame
cpower(): Power of Cox/log-rank Two-Sample Test
csv.get(): Read Comma-Separated Text Data Files
curveRep() print(<curveRep>) plot(<curveRep>) curveSmooth(): Representative Curves
cut2() cutGn(): Cut a Numeric Variable into Intervals
data.frame.create.modify.check: Tips for Creating, Modifying, and Checking Data Frames
dataRep() roundN() print(<dataRep>) predict(<dataRep>) print(<predict.dataRep>): Representativeness of Observations in a Data Set
deff(): Design Effect and Intra-cluster Correlation
describe(<vector>) describe(<matrix>) describe(<data.frame>) describe(<formula>) print(<describe>) latex(<describe>) latex(<describe.single>) html(<describe>) html(<describe.single>) formatdescribeSingle() plot(<describe>): Concise Statistical Description of a Vector, Matrix, Data Frame, or Formula
as.discrete() discrete() `[<-`(<discrete>) `[`(<discrete>) `[[`(<discrete>) is.discrete() `is.na<-`(<discrete>) `length<-`(<discrete>): Discrete Vector tools
dotchart2(): Enhanced Dot Chart
dotchart3() dotchartp() summaryD() summaryDp(): Enhanced Version of dotchart Function
dotchartpl(): Enhanced Version of dotchart Function for plotly
dualSD(): Dual Standard Deviations
ebpcomp(): ebpcomp
ecdfSteps(): ecdfSteps
mhgr() print(<mhgr>) lrcum() print(<lrcum>): Miscellaneous Functions for Epidemiology
equalBins(): Multicolumn Formating
errbar(): Plot Error Bars
escapeRegex() escapeBS(): Escapes any characters that would have special meaning in a reqular expression.
estSeqMarkovOrd(): estSeqMarkovOrd
estSeqSim(): estSeqSim
event.chart(): Flexible Event Chart for Time-to-Event Data
event.convert(): Event Conversion for Time-to-Event Data
event.history(): Produces event.history graph for survival data
extractlabs(): extractlabs
fImport(): fImport
find.matches() summary(<find.matches>) print(<find.matches>) matchCases(): Find Close Matches
first.word(): First Word in a String or Expression
format.df(): Format a Data Frame or Matrix for LaTeX or HTML
format.pval(): Format P Values
gbayes() plot(<gbayes>) gbayes2() gbayesMixPredNoData() gbayesMixPost() gbayesMixPowerNP() gbayes1PowerNP(): Gaussian Bayesian Posterior and Predictive Distributions
gbayesSeqSim(): gbayesSeqSim
geom_stepconfint(): Step function confidence intervals for ggplot2
getHdata(): Download and Install Datasets for Hmisc, rms, and Statistical Modeling
getRs(): Interact with github rscripts Project
getZip(): Open a Zip File From a URL
getabd(): getabd
colorFacet() arrGrob() print(<arrGrob>): Miscellaneous ggplot2 and grid Helper Functions
ggfreqScatter(): Frequency Scatterplot
ggplotlyr(): ggplotlyr
hashCheck(): hashCheck
hdquantile(): Harrell-Davis Distribution-Free Quantile Estimator
hidingTOC(): Moving and Hiding Table of Contents
hist(<data.frame>): Histograms for Variables in a Data Frame
histbackback(): Back to Back Histograms
histboxp() dhistboxp() histboxpM(): Use plotly to Draw Stratified Spike Histogram and Box Plot Statistics
hlab(): hlab
hlabs(): hlabs
hoeffd() print(<hoeffd>): Matrix of Hoeffding's D Statistics
html() htmlVerbatim(): Convert an S object to HTML
htmltabv(): htmltabc
impute() print(<impute>) summary(<impute>) is.imputed(): Generic Functions and Methods for Imputation
intMarkovOrd(): intMarkovOrd
knitrSet() plotlySave(): knitr Setup and plotly Service Function
labcurve() putKey() putKeyEmpty() drawPlot() plot(<drawPlot>) largest.empty(): Label Curves, Make Keys, and Interactively Draw Points and Curves
label() `label<-`() labelPlotmath() labelLatex() print(<labelled>) Label() llist() prList() putHfig() putHcap() plotmathTranslate() data.frame.labelled() relevel(<labelled>) reLabelled() combineLabels(): Label Attribute of an Object
latestFile(): latestFile
latex latex.default latex.function latex.list latexTranslate htmlTranslate latexSN htmlSN latexVerbatim dvi print.dvi dvi.latex dvips dvips.latex dvips.dvi dvigv dvigv.latex dvigv.dvi print.latex show.latex show.dvi: Convert an S object to LaTeX, and Related Utilities
latexCheckOptions(): Check whether the options for latex functions have been specified.
latexDotchart(): Enhanced Dot Chart for LaTeX Picture Environment with epic
latexTabular(): Convert a Data Frame or Matrix to a LaTeX Tabular
latexTherm() latexNeedle() pngNeedle(): Create LaTeX Thermometers and Colored Needles
Key() Key2() sKey(): Legend Creation Functions
list.tree(): Pretty-print the Structure of a Data Object
mApply(): Apply a Function to Rows of a Matrix or Vector
mChoice() format(<mChoice>) as.double(<mChoice>) print(<mChoice>) as.character(<mChoice>) summary(<mChoice>) print(<summary.mChoice>) `[`(<mChoice>) match.mChoice() inmChoice() inmChoicelike() nmChoice() is.mChoice() Summary(<mChoice>): Methods for Storing and Analyzing Multiple Choice Variables
makeNstr(): creates a string that is a repeat of a substring
mdb.get(): Read Tables in a Microsoft Access Database
meltData(): meltData
mgp.axis() mgp.axis.labels(): Draw Axes With Side-Specific mgp Parameters
minor.tick(): Minor Tick Marks
movStats(): movStats
mtitle(): Margin Titles
multLines(): Plot Multiple Lines
nCoincident(): nCoincident
na.delete(): Row-wise Deletion na.action
na.detail.response(): Detailed Response Variable Information
na.keep(): Do-nothing na.action
`%nin%`: Find Matching (or Non-Matching) Elements
nobsY(): Compute Number of Observations for Left Hand Side of Formula
nstr(): Creates a string of arbitry length
num.intercepts(): Extract number of intercepts
ordGroupBoot(): Minimally Group an Ordinal Variable So Bootstrap Samples Will Contain All Distinct Values
pMedian(): pMedian
pairUpDiff(): pairUpDiff
panel.bpplot() bpplt() bppltp() bpplotM(): Box-Percentile Panel Function for Trellis
partition.vector() partition.matrix(): Patitions an object into different sets
pc1(): First Principal Component
plot(<princmp>): plot.princmp
plotCorrM(): plotCorrM
plotCorrPrecision(): Plot Precision of Estimate of Pearson Correlation Coefficient
plotlyM(): plotly Multiple
plsmo(): Plot smoothed estimates
popower() print(<popower>) posamsize() print(<posamsize>) pomodm() simPOcuts() propsPO() propsTrans() multEventChart(): Power and Sample Size for Ordinal Response
princmp(): princmp
print(<char.list>): prints a list of lists in a visually readable format.
print(<char.matrix>): Function to print a matrix with stacked cells
print(<princmp>): print.princmp
printL(): printL
prn(): Print and Object with its Name
prselect(): Selectively Print Lines of a Text Vector
pstamp(): Date/Time/Directory Stamp the Current Plot
qcrypt(): qcrypt
qrxcenter(): qrxcenter
r2describe(): r2describe
rMultinom(): Generate Multinomial Random Variables with Varying Probabilities
rcorr() print(<rcorr>): Matrix of Correlations and P-values
rcorr.cens() rcorrcens(<formula>): Rank Correlation for Censored Data
rcorrp.cens() improveProb() print(<improveProb>): Rank Correlation for Paired Predictors with a Possibly Censored Response, and Integrated Discrimination Index
rcspline.eval(): Restricted Cubic Spline Design Matrix
rcspline.plot(): Plot Restricted Cubic Spline Function
rcspline.restate() rcsplineFunction(): Re-state Restricted Cubic Spline Function
reShape(): Reshape Matrices and Serial Data
redun() print(<redun>): Redundancy Analysis
rlegend() rlegendg(): Special Version of legend for R
rm.boot() plot(<rm.boot>): Bootstrap Repeated Measurements Model
rmClose(): rmClose
runParallel(): runParallel
runifChanged(): runifChanged
samplesize.bin(): Sample Size for 2-sample Binomial
sasxport.get() sasdsLabels(): Enhanced Importing of SAS Transport Files using read.xport
scat1d() jitter2() datadensity() histSpike() histSpikeg() ecdfpM(): One-Dimensional Scatter Diagram, Spike Histogram, or Density
score.binary(): Score a Series of Binary Variables
sedit() substring.location() replace.substring.wild() numeric.string() all.digits() substring2() `substring2<-`(): Character String Editing and Miscellaneous Character Handling Functions
seqFreq(): seqFreq
show.pch() show.col() character.table(): Display Colors, Plotting Symbols, and Symbol Numeric Equivalents
showPsfrag(): Display image from psfrag LaTeX strings
simMarkovOrd(): simMarkovOrd
simRegOrd(): Simulate Power for Adjusted Ordinal Regression Two-Sample Test
simplifyDims(): List Simplification
smean.cl.normal() smean.sd() smean.sdl() smean.cl.boot() smedian.hilow(): Compute Summary Statistics on a Vector
solvet(): solve Function with tol argument
somers2(): Somers' Dxy Rank Correlation
soprobMarkovOrd(): soprobMarkovOrd
soprobMarkovOrdm(): soprobMarkovOrdm
spikecomp(): spikecomp
spower() print(<spower>) Quantile2() print(<Quantile2>) plot(<Quantile2>) logrank() Gompertz2() Lognorm2() Weibull2(): Simulate Power of 2-Sample Test for Survival under Complex Conditions
spss.get(): Enhanced Importing of SPSS Files
src(): Source a File from the Current Working Directory
stat_plsmo(): Add a lowess smoother without counfidence bands.
stata.get(): Enhanced Importing of STATA Files
string.bounding.box(): Determine Dimensions of Strings
string.break.line(): Break a String into Many Lines at Newlines
stringDims(): String Dimentions
subplot(): Embed a new plot within an existing plot
summarize() asNumericMatrix() matrix2dataFrame(): Summarize Scalars or Matrices by Cross-Classification
summary(<formula>) `[`(<summary.formula.response>) print(<summary.formula.response>) plot(<summary.formula.response>) latex(<summary.formula.response>) print(<summary.formula.reverse>) plot(<summary.formula.reverse>) latex(<summary.formula.reverse>) print(<summary.formula.cross>) latex(<summary.formula.cross>) stratify() formula(<summary.formula.cross>) cumcategory() conTestkw() catTestchisq() ordTestpo(): Summarize Data for Making Tables and Plots
summaryM() print(<summaryM>) printsummaryM() plot(<summaryM>) latex(<summaryM>) html(<summaryM>): Summarize Mixed Data Types vs. Groups
summaryP() plot(<summaryP>) ggplot(<summaryP>) latex(<summaryP>): Multi-way Summary of Proportions
summaryRc(): Graphical Summarization of Continuous Variables Against a Response
summaryS() plot(<summaryS>) plotp(<summaryS>) mbarclPanel() medvPanel() mbarclpl() medvpl(): Summarize Multiple Response Variables and Make Multipanel Scatter or Dot Plot
symbol.freq(): Graphic Representation of a Frequency Table
sys(): Run Unix or Dos Depending on System
t.test.cluster() print(<t.test.cluster>): t-test for Clustered Data
tabulr() table_trio() table_freq() table_formatpct() nFm() table_latexdefs(): Interface to Tabular Function
testCharDateTime(): testCharDateTime
tex(): function for use in graphs that are used with the psfrag package in LaTeX
transace() print(<transace>) ggplot(<transace>) areg.boot() print(<areg.boot>) plot(<areg.boot>) smearingEst() summary(<areg.boot>) print(<summary.areg.boot>) predict(<areg.boot>) Function(<areg.boot>) Mean() Quantile(): Additive Regression and Transformations using ace or avas
transcan() summary(<transcan>) print(<transcan>) plot(<transcan>) ggplot(<transcan>) impute(<transcan>) fit.mult.impute() predict(<transcan>) Function() invertTabulated() vcov(<default>) vcov(<fit.mult.impute>): Transformations/Imputations using Canonical Variates
translate(): Translate Vector or Matrix of Text Strings
ceil() truncPOSIXt() roundPOSIXt(): Return the floor, ceiling, or rounded value of date or time to specified unit.
units() `units<-`(<default>): Units Attribute of a Vector
cleanup.import() upData() dataframeReduce(): Update a Data Frame or Cleanup a Data Frame after Importing
upFirst(): Change First Letters to Upper Case
valueTags() `valueTags<-`() valueLabel() `valueLabel<-`() valueName() `valueName<-`() valueUnit() `valueUnit<-`(): Store Descriptive Information About an Object
varclus() print(<varclus>) plot(<varclus>) naclus() naplot() plotMultSim() na.pattern(): Variable Clustering
vlab(): vlab
wtd.mean() wtd.var() wtd.quantile() wtd.Ecdf() wtd.table() wtd.rank() wtd.loess.noiter() num.denom.setup(): Weighted Statistical Estimates
Cbind() xYplot() panel.xYplot() prepanel.xYplot() Dotplot() prepanel.Dotplot() panel.Dotplot() setTrellis() numericScale(): xyplot and dotplot with Matrix Variables to Plot Error Bars and Bands
xtfrm(<labelled>): Auxiliary Function Method for Sorting and Ranking
xy.group(): Mean x vs. function of y in groups of x
yearDays() monthDays(): Get Number of Days in Year or Month
ynbind() pBlock(): Combine Variables in a Matrix