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20 binconf plot(ss, sds, xlab='Smoothing Parameter', ylab='SD of Imputed Values', type='b') abline(v=.2, lty=2) # default value of fweighted abline(h=rmse, lty=2) # root MSE of residuals from linear regression ## Not run: # Do a similar experiment for the Titanic dataset getHdata(titanic3) h
inconf 21 method include.x include.n return.df character string specifing which method to use. The "all" method only works when x and n are length 1. The "exact" method uses the F distribution to compute exact (based on the binomial cdf) intervals; the "wilson" interval is scoretest-based; and the "asymptotic" is the text-book, asymptotic normal interval. Following Agresti and Coull, the Wilson interval is to be preferred and so is the default. logical flag to indicate whether x should be included in the returned matrix or data frame logical flag to indicate whether n should be included in the returned matrix or data frame logical flag to indicate that a data frame rather than a matrix be returned Value a matrix or data.frame containing the computed intervals and, optionally, x and n. Author(s) Rollin Brant, Modified by Frank Harrell and Brad Biggerstaff Centers for Disease Control and Prevention National Center for Infectious Diseases Division of Vector-Borne Infectious Diseases P.O. Box 2087, Fort Collins, CO, 80522-2087, USA bkb5@cdc.gov References A. Agresti and B.A. Coull, Approximate is better than "exact" for interval estimation of binomial proportions, American Statistician, 52:119–126, 1998. R.G. Newcombe, Logit confidence intervals and the inverse sinh transformation, American Statistician, 55:200–202, 2001. L.D. Brown, T.T. Cai and A. DasGupta, Interval estimation for a binomial proportion (with discussion), Statistical Science, 16:101–133, 2001. Examples binconf(0:10,10,include.x=TRUE,include.n=TRUE) binconf(46,50,method="all")
Page 1 and 2: Package ‘Hmisc’ April 29, 2009
Page 3 and 4: R topics documented: 3 HmiscOvervie
Page 5 and 6: abs.error.pred 5 abs.error.pred Ind
Page 7 and 8: approxExtrap 7 Examples all.is.nume
Page 9 and 10: areg 9 y xtype ytype nk B na.rm tol
Page 11 and 12: areg 11 ## Not run: # Examine overf
Page 13 and 14: aregImpute 13 Usage A print method
Page 15 and 16: aregImpute 15 burnin pr plotTrans t
Page 17 and 18: aregImpute 17 Author(s) Frank Harre
Page 19: aregImpute 19 # plot(1:100, f$imput
Page 23 and 24: iVar 23 spearman2(formula, data=NUL
Page 25 and 26: ootkm 25 bootkm Bootstrap Kaplan-Me
Page 27 and 28: power 27 bsamsize(p1, p2, fraction=
Page 29 and 30: pplot 29 Description Producess side
Page 31 and 32: ystats 31 a missing value causes th
Page 33 and 34: ciapower 33 Value Returns a vector
Page 35 and 36: cnvrt.coords 35 Arguments x y input
Page 37 and 38: combine 37 ## create a subplot with
Page 39 and 40: contents 39 contents(object, dslabe
Page 41 and 42: cpower 41 Details Value For handlin
Page 43 and 44: csv.get 43 Description Makes a vect
Page 45 and 46: curveRep 45 Value a new data frame.
Page 47 and 48: curveRep 47 extrap pr which method
Page 49 and 50: curveRep 49 Examples ## Not run: #
Page 51 and 52: cut2 51 Usage cut2(x, cuts, m, g, l
Page 53 and 54: data.frame.create.modify.check 53 S
Page 55 and 56: data.frame.create.modify.check 55 #
Page 61 and 62: dataRep 61 Usage variables, the per
Page 63 and 64: describe 63 Usage deff(y, cluster)
Page 65 and 66: describe 65 may or may not have a r
Page 67 and 68: describe 67 #get quantiles .05,.10,
Page 69 and 70: dotchart2 69 Details as.discrete co
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dropUnusedLevels 71 xaxis set to FA
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Ecdf 73 Usage Ecdf(x, ...) ## Defau
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Ecdf 75 Value for Ecdf.default an i
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equalBins 77 equalBins Multicolumn
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errbar 79 panel.first panel.last as
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event.chart 81 event.chart Flexible
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event.chart 83 or an S-Plus dates o
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event.chart 85 If "custom" is chose
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event.chart 87 subset.c) specified
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event.chart 89 Dubin, J.A., Lee, J.
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event.convert 91 # To produce more
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event.history 93 Description Usage
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event.history 95 the individual rig
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event.history 97 plot(heart.surv, y
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find.matches 99 ## S3 method for cl
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find.matches 101 # For many applica
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format.df 103 Value a character str
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format.df 105 \tabular environment
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gbayes 107 gbayes Gaussian Bayesian
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gbayes 109 sd prior pcdf delta v n1
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gbayes 111 stat
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getHdata 113 # Get the posterior de
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getZip 115 Examples ## Not run: get
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hist.data.frame 117 Author(s) Frank
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histbackback 119 Arguments Value x,
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HmiscOverview 121 ciapower cleanup.
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HmiscOverview 123 minor.tick mtitle
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HmiscOverview 125 sys tex transace
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hoeffd 127 Usage hoeffd(x) hoeffd(x
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html 129 file name of the file to c
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inc-dec 131 Value object ... ignore
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labcurve 133 To add a legend defini
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labcurve 135 y for putKeyEmpty and
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labcurve 137 lwd col. col transpare
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labcurve 139 Value key is called on
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label 141 # Use the mouse to draw a
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label 143 Arguments x Value self un
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latex 145 Details A.ttributes of th
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latex 147 caption=NULL, caption.lot
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latex 149 cgroup n.cgroup rgroup n.
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latex 151 booktabs table.env here l
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latex 153 PATH=paste(Sys.getenv("PA
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ldBands 155 Usage Lan. Such stoppin
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ldBands 157 Value A list of class "
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makeNstr 159 Arguments struct depth
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mChoice 161 Value For mApply, the r
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mChoice 163 table a vector (mChoice
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mdb.get 165 # could also do: # summ
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mgp.axis 167 Arguments side at see
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mhgr 169 Author(s) Frank E Harrell
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Misc 171 Author(s) Frank Harrell De
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Misc 173 outerText(string, y, setAs
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mtitle 175 set.seed(1) whichClosest
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na.detail.response 177 Usage na.del
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na.keep 179 # age=NA age!=NA sex!=N
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panel.bpplot 181 Examples nstr(c("a
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panel.bpplot 183 Author(s) Frank Ha
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pc1 185 See Also split Examples a
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plsmo 187 plsmo Plot smoothed estim
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plsmo 189 type pch cex font set to
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print.char.list 191 Value a list co
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print.char.matrix 193 print.char.ma
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ps.slide 195 Arguments x txt any ob
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ps.slide 197 strip.blank =TRUE, lty
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ps.slide 199 Value ratio lref psref
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corr 201 Details Certain functions
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corr.cens 203 Usage rcorr.cens(x, S
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corrp.cens 205 abline(h=.5, v=0, co
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cspline.eval 207 rcspline.eval Rest
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cspline.plot 209 nk knots show adj
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cspline.restate 211 after begin nbe
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edun 213 minfreq iterms pc pr For a
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equirePackage 215 Examples x
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eShape 217 colvar base reps times t
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legend 219 # d
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m.boot 221 rm.boot Bootstrap Repeat
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m.boot 223 smoother xlab xlim ylim
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m.boot 225 Details Value ordered by
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m.boot 227 n
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samplesize.bin 229 Description Give
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sasxport.get 231 Usage used, it is
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Save 233 # output; # format d1 mmdd
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scat1d 235 jitter2.default for vect
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scat1d 237 lwd col y curve line wid
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scat1d 239 Details For scat1d the l
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score.binary 241 # datadensity.data
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sedit 243 substring2(text, first, l
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show.pch 245 x
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smean.sd 247 smean.sd Compute Summa
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somers2 249 Arguments a b tol a squ
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spower 251 Usage The Weibull2 funct
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spower 253 Value spower returns the
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spss.get 255 set.seed(211) spower(r
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stata.get 257 Arguments x an unquot
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store 259 store Store an Object Per
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string.break.line 261 Value rows co
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subplot 263 subplot Embed a new plo
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summarize 265 Usage summarize store
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summarize 267 dfr
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summary.formula 269 summary.formula
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summary.formula 271 rowlabel = '',
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summary.formula 273 overall continu
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summary.formula 275 dotfont font fo
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summary.formula 277 subtitles capti
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summary.formula 279 bpplt() # annot
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summary.formula 281 y
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symbol.freq 283 summary(age ~ stage
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t.test.cluster 285 Side Effects exe
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transace 287 against the lowest lev
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transace 289 categorical binary pl
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transace 291 Details Value As trans
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transace 293 newdat
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transcan 295 values of the target v
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transcan 297 ## S3 method for class
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transcan 299 impcat mincut inverse
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transcan 301 rhsImp Set to ‘"rand
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transcan 303 freq aty a vector of f
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transcan 305 categorical asis coef
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transcan 307 blood.pressure=60:260,
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translate 309 x[1:500]
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units 311 Value An object of class
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upData 313 The dataframeReduce func
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upData 315 fracmiss maxlevels minpr
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varclus 317 For valueTag
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varclus 319 df s similarity type me
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varclus 321 description, and naplot
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wtd.stats 323 Usage expand x by the
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wtd.stats 325 Author(s) Frank Harre
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xYplot 327 xYplot xyplot and dotplo
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xYplot 329 probs=c(.5,.25,.75), nx=
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xYplot 331 Details Value minor.tick
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xYplot 333 xYplot(Cbind(y,lower,upp
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yearDays 335 setTrellis() # blank c
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Index ∗Topic IO csv.get, 40 getZi
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INDEX 339 ∗Topic iplot labcurve,
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INDEX 341 (summary.formula), 266 [.
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INDEX 343 is.discrete (discrete), 6
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INDEX 345 print.dvi (latex), 142 pr
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INDEX 347 units
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