ChineseEdition
0.1
EmmanuelParadis
´InstitutdesSciencesdel’Evolution
Universit´eMontpellierIIF-34095Montpellierc´edex05France
E-mail:paradis@isem.univ-montp2.fr
Co-translatedby:XFWang,YHXie,JTLiandGHDing
“Rforbeginners”
2002
R
2005
EmmanuelParadis
Chap1–2:
ALTEXChap3:
Chap4:
Chap5–7:
pwxf@hotmail.com
20063
c2002,2005,EmmanuelParadis
Permissionisgrantedtomakeanddistributecopies,eitherinpartorin
fullandinanylanguage,ofthisdocumentonanysupportprovidedtheabovecopyrightnoticeisincludedinallcopies.Permissionisgrantedtotranslatethisdocument,eitherinpartorinfull,inanylanguageprovidedtheabovecopyrightnoticeisincluded.
12
2.1..............................
2.2.....................
2.3..............................
3R
3.1.........
........................3.2.
........................3.3..............................3.4
......
........................3.4.1..........................3.4.2..
........................3.5
......
........................3.5.1..........................3.5.2..........................3.5.3.....
........................3.5.4.............3.5.5......................3.5.6..........
...............3.5.7.
...............3.5.8
...........
.
.
.............
4
R4.1
..........
.
...................4.1.1
.....................4.1.2
.........................4.2..........
....................4.3...........................4.4..............................4.5..........
....................4.6
gridlattice
...........................
13
357991114151518191924262730323234373737384142444549
5R
5.15.25.35.46R
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............
........................................................................................
5656575962
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65
............................65..............................67
6.37R
.........................68
71
1
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http://cran.r-project.org/doc/FAQ/R-FAQ.html4
Formoreinformation:http://www.gnu.org/5
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1
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8
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12
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14
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3.4
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15
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Read9items>z
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7
8
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1
2
3
4
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length
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16
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>gl(2,6,label=c(\"Male\\"Female\"))[1]MaleMaleMaleMaleMaleMale[7]FemaleFemaleFemaleFemaleFemaleFemaleLevels:MaleFemale>gl(2,10)
[1]11111111112222222222Levels:12
>gl(2,1,length=20)
[1]12121212121212121212Levels:12
>gl(2,2,length=20)
[1]11221122112211221122Levels:12
expand.grid()
>expand.grid(h=c(60,80),w=c(100,300),sex=c(\"Male\\"Female\"))
hwsex160100Male280100Male360300Male480300Male560100Female680100Female760300Female880300Female
17
3.4.2
Gaussian(normal)exponentialgammaPoissonWeibullCauchybeta
‘Student’(t)
Fisher–Snedecor(F)Pearson(χ2)binomialmultinomialgeometric
hypergeometriclogisticlognormal
negativebinomialuniform
Wilcoxon’sstatisticsrnorm(n,mean=0,sd=1)rexp(n,rate=1)
rgamma(n,shape,scale=1)rpois(n,lambda)
rweibull(n,shape,scale=1)
rcauchy(n,location=0,scale=1)rbeta(n,shape1,shape2)rt(n,df)
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rbinom(n,size,prob)rmultinom(n,size,prob)rgeom(n,prob)
rhyper(nn,m,n,k)
rlogis(n,location=0,scale=1)rlnorm(n,meanlog=0,sdlog=1)rnbinom(n,size,prob)runif(n,min=0,max=1)
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0 >qnorm(0.025)[1]-1.959964>qnorm(0.975)[1]1.959964 qnorm(0.05) 1- qnorm(0.95) 18 P df=1χ2=3.84 >1-pchisq(3.84,1)[1]0.05004352 3.5 3.5.1 c() (p.27) lm R Vector vector (mode) (length) \"\" 0 FALSE numeric() logical() character() Factor factor factor(x,levels=sort(unique(x),na.last=TRUE), labels=levels,exclude=NA,ordered=is.ordered(x))levels x exclude x labelsordered x >factor(1:3)[1]123 19 Levels:123 >factor(1:3,levels=1:5)[1]123 Levels:12345 >factor(1:3,labels=c(\"A\\"B\\"C\"))[1]ABC Levels:ABC >factor(1:5,exclude=4)[1]123NA5Levels:1235 levels >ff<-factor(c(2,4),levels=2:5)>ff[1]24 Levels:2345>levels(ff) [1]\"2\"\"3\"\"4\"\"5\" Matrix dim 2 matrix matrix(data=NA,nrow=1,ncol=1,byrow=FALSE, dimnames=NULL) byrow TRUE dimnames >matrix(data=5,nr=2,nc=2) [,1][,2][1,]55[2,]55 >matrix(1:6,2,3) [,1][,2][,3][1,]135[2,]246 >matrix(1:6,2,3,byrow=TRUE) [,1][,2][,3][1,]123[2,]456 20 NULL >x<-1:15>x [1]123456789101112131415 >dim(x)NULL >dim(x)<-c(5,3)>x [,1][,2][,3][1,]1611[2,]2712[3,]3813[4,]4914[5,]51015Dataframetable data.frame >x<-1:4;n<-10;M<-c(10,35);y<-2:4 >data.frame(x,n)xn1110221033104410 >data.frame(x,M)xM1110223533104435 >data.frame(x,y) Errorindata.frame(x,y): argumentsimplydifferingnumberofrows:4,3 data.frame(A1=x,A2=n) 21 read. row.names List list data.frame() x y >L1<-list(x,y);L2<-list(A=x,B=y) >L1[[1]] [1]1234[[2]] [1]234>L2$A [1]1234$B [1]234>names(L1)NULL >names(L2)[1]\"A\"\"B\" Time-series ts ts ts(data=NA,start=1,end=numeric(0),frequency=1, deltat=1,ts.eps=getOption(\"ts.eps\"),class,names) 22 datastartend frequencydeltat start 1/12 frequency deltat ts.epsclassnames ts.eps \"ts\" c(\"mts\\"ts\") data Series1, Series2,... ts >ts(1:10,start=1959)TimeSeries:Start=1959End=1968Frequency=1 [1]12345678910 >ts(1:47,frequency=12,start=c(1959,2)) JanFebMarAprMayJunJulAugSepOctNovDec19591234567891011196012131415161718192021222319612425262728293031323334351962363738394041424344454647>ts(1:10,frequency=4,start=c(1959,2)) Qtr1Qtr2Qtr3Qtr419591231960456719618910 >ts(matrix(rpois(36,5),12,3),start=c(1961,1),frequency=12) Series1Series2Series3 Jan1961854Feb1961669Mar1961233 23 AprMayJunJulAugSepOctNovDec196119611961196119611961196119611961Expression 84441166585962655554313647772R R expresssion eval() >x<-3;y<-2.5;z<-1 >exp1<-expression(x/(y+exp(z)))>exp1 expression(x/(y+exp(z)))>eval(exp1)[1]0.5749019 (p.43) D >D(exp1,\"x\")1/(y+exp(z))>D(exp1,\"y\")-x/(y+exp(z))^2>D(exp1,\"z\") -x*exp(z)/(y+exp(z))^23.5.2 R 2.1.0 baseutils as.something 98 24 as.numeric as.logical FALSE TRUE \"1\",\"2\",... \"A\",... 0 \"FALSE\",\"F\"\"TRUE\",\"T\" as.character 1,2,...FALSETRUE →→→→→→→→→→→→01 1,2,...NAFALSETRUEFALSETRUENA \"1\",\"2\",...\"FALSE\"\"TRUE\" (as.matrix,as.ts,as.data.frame, as.expression,...) R R >fac<-factor(c(1,10))>fac[1]110 Levels:110 >as.numeric(fac)[1]12 >fac2<-factor(c(\"Male\\"Female\"))>fac2[1]MaleFemaleLevels:FemaleMale>as.numeric(fac2)[1]21 NA 25 >as.numeric(as.character(fac))[1]110 read.table() 3.5.3 10 R+ x&y*<=x&&y/>=x|y^==x||y %%!= xor(x,y) %/% (x+y,a ! ) & |&& || 0 (1 0<1) >x<-0.5>0 R $,@,[,[[,:,?,<-,<<-,=,:: ?Syntax 26 0 all.equal >x<-1:3;y<-1:3>x==y [1]TRUETRUETRUE>identical(x,y)[1]TRUE >all.equal(x,y)[1]TRUE identical FALSEall.equalTRUE >0.9==(1-0.1)[1]TRUE >identical(0.9,1-0.1)[1]TRUE >all.equal(0.9,1-0.1)[1]TRUE >0.9==(1.1-0.2)[1]FALSE >identical(0.9,1.1-0.2)[1]FALSE >all.equal(0.9,1.1-0.2)[1]TRUE >all.equal(0.9,1.1-0.2,tolerance=1e-16)[1]\"Meanrelativedifference:1.233581e-16\"3.5.4 x x[3] >x<-1:5 >x[3][1]3 >x[3]<-20 27 TRUE 3 >x[1] 122045 >i<-c(1,3)>x[i][1]120 x i j x[i,j] >x<-matrix(1:6,2,3)>x [,1][,2][,3][1,]135[2,]246>x[,3]<-21:22>x [,1][,2][,3][1,]1321[2,]2422>x[,3][1]2122 R drop TRUE: >x[,3,drop=FALSE] [,1][1,]21[2,]22 x[i,j,k],x[,,3],x[,,3,drop=FALSE] >x(1) Error:couldn’tfindfunction\"x\" 28 x[-1, ] x[-c(1,15),] 1 15 >x[,-1] [,1][,2][1,]321[2,]422>x[,-(1:2)][1]2122 >x[,-(1:2),drop=FALSE] [,1][1,]21[2,]22 >x<-1:10>x[x>=5]>x [1]12>x[x==1]>x [1]252 <-20 34202020202020<-253 4202020202020 >x<-rpois(40,lambda=5)>x [1]59477645113[21]4665453433>x[x%%2==0] [1]464222466448424 53771753389124225124 >x<-1:40 >s<-c(FALSE,TRUE)>x[s] [1]246810121416182022242628303234363840 29 3 my.list[[3]][i] my.list[[3]][i,j,k] 12 my.list[1:2] my.list[[1:2]] 3.5.5 names(names,colnames,rownames,dimnames) names >x<-1:3 >names(x)NULL >names(x)<-c(\"a\\"b\\"c\")>xabc123 >names(x) [1]\"a\"\"b\"\"c\">names(x)<-NULL>x [1]123 colnames rownamesdimnames >X<-matrix(1:4,2) >rownames(X)<-c(\"a\\"b\")>colnames(X)<-c(\"c\\"d\")> Xcda13b24 >dimnames(X) 30 names [[1]] [1]\"a\"\"b\"[[2]] [1]\"c\"\"d\" dimnames >A<-array(1:8,dim=c(2,2,2))>A,,1 [,1][,2][1,]13[2,]24,,2 [,1][,2][1,]57[2,]68 >dimnames(A)<-list(c(\"a\\"b\"),c(\"c\\"d\"),c(\"e\\"f\"))>A,,ecda13b24,,fcda57b68 DF[\"x\"] x DF DF[c(\"x\\"y\")] x y z 31 $( DF$x) 3.5.6 X data.entry(X) data.entry de 3.5.7 R c >c(1:5,seq(10,11,0.2)) [1]1.02.03.04.05.010.010.210.410.610.811.0 >x>y>z>z[1] <-1:4 <-rep(1,4)<-x+y2345 >x>y>z>z[1]>x>y <-1:4<-1:2<-x+y2446<-1:3<-1:2 32 >z<-x+y Warningmessage:longerobjectlength isnotamultipleofshorterobjectlengthin:x+y>z [1]244 R >x>a>z>z[1] <-1:4<-10<-a*x10203040R abs,sqrt,...), (log,exp,log10,log2,sin,cos,tan,asin,acos,atan, (gamma,digamma,beta,besselI,...) sum(x)prod(x)max(x)min(x) which.max(x)which.min(x)range(x)length(x)mean(x)median(x) var(x)orcov(x)cor(x) var(x,y)orcov(x,y)cor(x,y) xx xx xx c(min(x),max(x)) xxxx n−1 x x xxy 1 x y x y ( 1 ) range 33 2 var,cov, cor round(x,n)rev(x)sort(x)rank(x) log(x,base)scale(x) xxx n rev(sort(x)) x base x x pmin(x,y,...)pmax(x,y,...)cumsum(x)cumprod(x)cummin(x)cummax(x)match(x,y)which(x==a) center=FALSE center=TRUE,scale=TRUE i scale=FALSE x[i],y[i],...x[1] x[i] i x x y y NA x TRUE i x[i]==a choose(n,k)na.omit(x)na.fail(x)unique(x)table(x)table(x,y)subset(x,...) n k NA x xx NA x ( ) (... x y x x$V1<10 x select sample(x,size) size replace=TRUE 3.5.8 R rbind() cbind() >m1<-matrix(1,nr=2,nc=2) 34 >m2<-matrix(2,nr=2,nc=2)>rbind(m1,m2) [,1][,2][1,]11[2,]11[3,]22[4,]22>cbind(m1,m2) [,1][,2][,3][,4][1,]1122[2,]1122 %*% >rbind(m1,m2)%*%cbind(m1,m2) [,1][,2][,3][,4][1,]2244[2,]2244[3,]4488[4,]4488 >cbind(m1,m2)%*%rbind(m1,m2) [,1][,2][1,]1010[2,]1010 t diag >diag(m1)[1]11 >diag(rbind(m1,m2)%*%cbind(m1,m2))[1]2288 >diag(m1)<-10>m1 [,1][,2][1,]101[2,]110>diag(3) [,1][,2][,3][1,]100 35 m1 m2 [2,]010[3,]001>v<-c(10,20,30)>diag(v) [,1][,2][,3][1,]1000[2,]0200[3,]0030 >diag(2.1,nr=3,nc=5) [,1][,2][,3][,4][,5][1,]2.10.00.000[2,]0.02.10.000[3,]0.00.02.100 R qr eigen 36 solve svd 4 R R demo(persp) :demo(graphics) R 11 graphicaldevice high-levelplottingfunctions low-levelplottingfunctionsgraphicalparameters par grid lattice 4.1 4.1.1 R Unix/Linux x11 Windows windows Windows x11() windows()postscript(), pdf(),png(),... ?device dev.list() >x11();x11();pdf()>dev.list()X11X11pdf234 11 :hist() barplot() 37 >dev.cur()pdf4 >dev.set(3)X113 dev.off() R >dev.off(2)X113 >dev.off()pdf4 R Widows win.metafile “History” “Recording” WindowsMetafile 4.1.2 split.screen >split.screen(c(1,2)) screen(1) screen(2)erase.screen() split.screen() layout() coplot() layout “sub-windows” 4 >layout(matrix(1:4,2,2)) 38 >mat<-matrix(1:4,2,2)>mat [,1][,2][1,]13[2,]2>layout(mat) 4 layout.show 4 13 >layout.show(4) 2 4 layout() >layout(matrix(1:6,3,2))>layout.show(6) 123 456 >layout(matrix(1:6,2,3))>layout.show(6) 135 246 >m<-matrix(c(1:3,3),2,2)>layout(m) >layout.show(3) 1 3 2 matrix()byrow matrix(...,byrow=TRUE) matrix(c(2,1,4,3), 2,2) layout()widths heights ( ?layout) >m<-matrix(1:4,2,2)>layout(m,widths=c(1,3), heights=c(3,1)) >layout.show(4) 39 13 24 >m<-matrix(c(1,1,2,1),2,2)>layout(m,widths=c(2,1), heights=c(1,2)) >layout.show(2) 2 1 0 >m<-matrix(0:3,2,2) >layout(m,c(1,3),c(1,3))>layout.show(3) >m<-matrix(scan(),5,5)1:003331133311:003330220521:4220526: Read25items>layout(m) >layout.show(5) 2 13 1 4 2 3 5 40 4.2 R : plot(x)plot(x,y) sunflowerplot(x,y) pie(x) boxplot(x)stripchart(x)coplot(x~y|z)interaction.plot(f1,f2,y)matplot(x,y)dotchart(x) fourfoldplot(x)assocplot(x)mosaicplot(x)pairs(x)plot.ts(x)ts.plot(x)hist(x)barplot(x)qqnorm(x)qqplot(x,y) contour(x,y,z) x-x(x-) x(y-y(y-) ) x (“box-and-whiskers”)(boxplot())zxyf1f2f1x-yy-fun fun=meanxyx f2 y y x Cleveland x dim=c(2, 2,k) Cohen–Friendly‘mosaic’ xx\"ts\" dim=c(2,2) k=1 x x x x xx x x y xy dim(z)=c(length(x),length(y))x z y filled.contour(x,y,z) image(x,y,z)persp(x,y,z)stars(x) symbols(x,y,...)termplot(mod.obj) x x x y “boxplots” mod.obj 41 R add=FALSEaxes=TRUEtype=\"p\" TRUEFALSE \"p\": \"l\": \"h\":\"S\": \"b\":\"s\": \"o\": xlim=,ylim=xlab=,ylab=main=sub= xlim=c(1,10) xlim=range(x) 4.3 R (low-levelplottingcommands) : points(x,y)lines(x,y) text(x,y,labels,...) mtext(text, side=3,line=0,...) segments(x0,y0,x1,y1) arrows(x0,y0, x1,y1,angle=30,code=2) abline(a,b)abline(h=y)abline(v=x)abline(lm.obj)rect(x1,y1,x2,y2) polygon(x,y)legend(x,y,legend)title() axis(side,vect) type= (x,y)labels type=\"n\");text(x,y,names) text axis()line :plot(x,y, side (x0,y0) (x1,y1) code=2 (x1,y1) (x0,y0) code=3;angle code=1 b a y abcissaxlm.obj x1,x2,y1, y2 x y (x,y) legend (side=1)vect (2) abcissa (3) (4) 42 box()rug(x) locator(n, type=\"n\...) x- x (...) (type=\"n\") n (type=\"p\") (x,y) (type=\"l\") text(x,y,expression(...))expression >text(x,y,expression(p==over(1,1+e^-(beta*x+alpha)))) (x,y) : p= 1+e−(βx+α) 1 R2 Rsquared >text(x,y,as.expression(substitute(R^2==r,list(r=Rsquared)))) (x,y) R2=0.9856298 3 >text(x,y,as.expression(substitute(R^2==r,+list(r=round(Rsquared,3))))) R2=0.986 R >text(x,y,as.expression(substitute(italic(R)^2==r,+list(r=round(Rsquared,3))))) R2=0.986 43 4.4 par >par(bg=\"yellow\") 73 ?par adj 0 0.5 1 >1 c(0,0)) bgbtycexcolfontlaslty bg=\"red\",bg=\"blue\"; colors() 657 :\"o\",\"l\",\"7\",\"c\",\"u\"ou\"]\" bty=\"n\" cex.labcex.maincex.subcexcol.axis,col.lab,col.main,col.sub1:2:3:4:cex font.axis,font.lab,font.main,font.sub 0:1:2:3: 1:2:3:4:5: 6:8\"0\"\"9\" lty=\"44\"lty=2 cex.axis : lwdmarmfcolmfrowpchpsptytcktclxaxtyaxt 4 c(5.1,4.1,4.1,2.1) c(nr,nc)4.1.2 c(bottom,left,top,right), nr nc 4.1.2 125 \"\" 2 \"s\": \"m\": tck=1 xaxt=\"n\"yaxt=\"n\" x-y- tcl=-0.5 axis(side=1,...)axis(side=2,...) 44 12345678910 111213141516171819202122232425 \"*\" \"?\"\".\"\"X\"\"a\" * Figure2: ? Xa R(pch=1:25) 21–25 col=\"blue\bg=\"yellow\" pch=\"*\", \"?\",\".\",... 4.5 R 10 >x<-rnorm(10)>y<-rnorm(10) plot() >plot(x,y) 3 R plot(x,y,xlab=\"Tenrandomvalues\ylab=\"Tenothervalues\ xlim=c(-2,2),ylim=c(-2,2),pch=22,col=\"red\bg=\"yellow\bty=\"lcl=0.4, main=\"HowtocustomizeaplotwithR\las=1,cex=1.5) 45 y−1.0−0.5 −0.50.00.50.0 x 0.51.0 Figure3: plot 4 xlab ylab xlim 12 pch ylimpch=22 col bg bty,tcl,las cex main plot par() 5 opar<-par()par(bg=\"lightyellow\col.axis=\"blue\mar=c(4,4,2.5,0.25))plot(x,y,xlab=\"Tenrandomvalues\ylab=\"Tenothervalues\ xlim=c(-2,2),ylim=c(-2,2),pch=22,col=\"red\bg=\"yellow\bty=\"lcl=-.25,las=1,cex=1.5) title(\"HowtocustomizeaplotwithR(bis)\font.main=3,adj=1)par(opar) opar bg col.axis mar 12 xaxs=\"i\" R yaxs=\"i\" 4%plot() 46 How to customize a plot with R 2 1Ten other values0 −1 −2 −2 −1 0 Ten random values 1 2 Figure4: plot How to customize a plot with R (bis)21Ten other values0−1−2−2−10Ten random values12Figure5: par plot title 47 4title 5 R plot(...,type=\"n\") 6 opar<-par()par(bg=\"lightgray\mar=c(2.5,1.5,2.5,0.25))plot(x,y,type=\"n\xlab=\"\ylab=\"\xlim=c(-2,2), ylim=c(-2,2),xaxt=\"n\yaxt=\"n\") rect(-3,-3,3,3,col=\"cornsilk\")points(x,y,pch=10,col=\"red\cex=2)axis(side=1,c(-2,0,2),tcl=-0.2,labels=FALSE) axis(side=2,-1:1,tcl=-0.2,labels=FALSE)title(\"HowtocustomizeaplotwithR(ter)\ font.main=4,adj=1,cex.main=1) mtext(\"Tenrandomvalues\side=1,line=1,at=1,cex=0.9,font=3)mtext(\"Tenothervalues\line=0.5,at=-1.8,cex=0.9,font=3)mtext(c(-2,0,2),side=1,las=1,at=c(-2,0,2),line=0.3, col=\"blue\cex=0.9) mtext(-1:1,side=2,las=1,at=-1:1,line=0.2,col=\"blue\cex=0.9)par(opar) type=\"n\" xaxt=\"n\yaxt=\"n\" xlimylim xlab=\"\ axes=FALSE rect() points() axis() labels=FALSE labels=c(\"A\\"B\ \"C\") title() mtext() line mtext()side(3) line=0 mtext() at 48 Ten other valuesHow to customize a plot with R (ter)10−1−20Ten random values2Figure6: 4.6grid lattice gridandlattice •• viewports (grob) gridBase R S-PLUS Trellis Trellis 13 Trellis coplot latticey~x 14 y~x|z y x z http://cm.bell-labs.com/cm/ms/departments/sia/project/trellis/index.htmlplot()xyplot(y~x)plot(x,y) 14 13 49 lattice (y~x|z) z barchart(y~x)bwplot(y~x)densityplot(~x)dotplot(y~x)histogram(~x)qqmath(~x) stripplot(y~x)qq(y~x) xyplot(y~x) levelplot(z~x*y)contourplot(z~x*y)cloud(z~x*y) wireframe(z~x*y)splom(~x)parallel(~x) x y Clevelandx ( ) x x y x y ” ”y z z x y x 3-D lattice library(lattice) densityplot(~x) x- rug() panel n<-seq(5,45,5)x<-rnorm(sum(n))y<-factor(rep(n,n),labels=paste(\"n=\n))densityplot(~x|y, panel=function(x,...){ panel.densityplot(x,col=\"DarkOliveGreen\...)panel.mathdensity(dmath=dnorm, args=list(mean=mean(x),sd=sd(x)),col=\"darkblue\") }) 45 densityplot 5,10,15,...,panel panel.densityplot lattice panel.mathdensity panel.densityplot 50 −4−2024n = 350.60.50.40.30.20.10n = 40n = 45n = 20n = 25n = 300.60.5Density0.40.30.20.10n = 50.60.50.40.30.20.10−4−2024n = 10n = 15−4−2024xFigure7: densityplot panel densityplot(~x|y) 7 lattice R 1000 8 data(quakes)mini<-min(quakes$depth)maxi<-max(quakes$depth)int<-ceiling((maxi-mini)/9)inf<-seq(mini,maxi,int) quakes$depth.cat<-factor(floor(((quakes$depth-mini)/int)), labels=paste(inf,inf+int,sep=\"-\")) xyplot(lat~long|depth.cat,data=quakes) ( quakesdepth) 5 data xyplot xyplot 15 iris 9 data(iris)xyplot( Petal.Length~Petal.Width,data=iris,groups=Species,panel=panel.superpose, plot()~quakes$lat) 15 data , plot(quakes$long 51 165170175180185472−544−10−15−20−25−30−35−40544−616616−688256−328328−400400−472−10−15t−20al−25−30−3540−112112−184184−256−40−10−15−20−25−30−35−40165170175180185165170175180185longFigure8: quakes xyplot type=c(\"p\\"smooth\"),span=.75,auto.key=list(x=0.15,y=0.85)) xyplotgroupspanel panel.superpose panel.superposetypeplot() \"p\" \"smooth\" spanauto.key [0,1] splom iris 10 splom( ~iris[1:4],groups=Species,data=iris,xlab=\"\panel=panel.superpose, auto.key=list(columns=3)) iris pairs splom“ScatterPlotMatrix” xlab=\"\" 52 x-7ooooooooooooooooooooooooooooo6setosaversicolorvirginicaoooooooooooooooooooo5oooooooooooooooooooPetal.Length4ooooooooooo3o2oo1oooooooooooooooooooo00.511.522.5Petal.WidthFigure9: iris xyplot SetosaooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooVersicolorVirginicaoooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo2.521.51.522.5Petal.Width10.5ooooooooooooooooooooooooooooooooooooooo0oooooooooooo7oo4567oooooooooooooooo6oooooooooooooooooooooooooooooooooooooooooooooo5oooooooooooooooooooooooooooooooooooooooooooooooooooooooooo4Petal.Length4oooooooooooooooooooo3ooo4.543.5oooooooooooooooooooo1oooooo3.54223410.510ooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo8787ooooooooooooooooooooooooooooooooooooooooooSepal.Width4.5ooooooooooooooooooooooooooooooooo3oo2.5o22.532Sepal.Length6556oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooFigure10: iris 1 splom 53 virginicaPetalLengthSepalWidthSepalLengthsetosaPetalLengthversicolorPetalLengthSepalWidthSepalWidthSepalLengthSepalLengthScatter Plot MatrixFigure11: iris 2 splom auto.key columns=3 3 10 pairs() Fig.11 splom(~iris[1:3]|Species,data=iris,pscales=0, varnames=c(\"Sepal\\nLength\\"Sepal\\nWidth\\"Petal\\nLength\")) pscales= 0 \"\\n\" y- iris 12 parallel(~iris[,1:4]|Species,data=iris,layout=c(3,1)) 54 MinMaxsetosaPetal.WidthversicolorvirginicaPetal.LengthSepal.WidthSepal.LengthMinMaxMinMaxFigure12: iris parallel 55 5R R . R . stats, , ( , , ), , . , R , . R , .stats, R , , (formulae). (genericfunctions). 5.1 stats :InsectSprays. . aov. , R ,. 12 , 72 , . data , : >data(InsectSprays) >aov.spray<-aov(sqrt(count)~spray,data=InsectSprays) aov (~ InsectSprays ) . . data=InsectSprays . : >aov.spray<-aov(sqrt(InsectSprays$count)~InsectSprays$spray) , : >aov.spray<-aov(sqrt(InsectSprays[,1])~InsectSprays[,2]) , , . 56 , aov.spray. , ( ), printsummary ( ): >aov.sprayCall: aov(formula=sqrt(count)~spray,data=InsectSprays)Terms: sprayResiduals SumofSquares88.4378726.05798Deg.ofFreedom 5 66 Residualstandarderror:0.6283453Estimatedeffectsmaybeunbalanced >summary(aov.spray) DfSumSqMeanSqFvaluePr(>F) spray588.43817.68844.799<2.2e-16***Residuals26.0580.395---Signif.codes:0‘***’0.001‘**’0.01‘*’0.05‘.’0.1‘’1 print(aov.spray) .plot()termplot() . plot(aov.spray), , 16. : >opar<-par() >par(mfcol=c(2,2))>plot(aov.spray)>par(opar) >termplot(aov.spray,se=TRUE,partial.resid=TRUE,rug=TRUE) 13 14 . 5.2 17R : . y~model, y ,model 16 17 : layout : , . 57 66 Standardized residualsResiduals vs Fitted Residuals1.02739 Scale−Location plot 1.5272539 0.0−1.5251.52.5Fitted values 3.5 0.01.5 0.51.02.5Fitted values 3.5 Standardized residualsNormal Q−Q plot 0.08Cook’s distance23927Cook’s distance plot 272539125−2−1012 0.000 −20.040204060 Theoretical QuantilesObs. number Figure13: plot() aov . . . bX,,X[,1]+X[,2]+...+X[,ncol(X)]; (,X[,2:4]) ab (a+b+a:b) an ,n,(a+b+c)^2 a+b+c+a:b+a:c+b:c (a+a:b,a/b)ba b,:(a+b+c)^2-a:b a+b+c+a:c+b:c (y~x+0y~x-1 0+y~x) ()y~1 ( offset(3*x))a a+bX a:ba*b poly(a,n)^nb%in%a-b-1 1 offset(...) ,. R , , + , y~x1+x2y=β1x1+β2x2+α,()y=β(x1+x2)+α. I:y~I(x1+x2)y=β(x1+x2)+α. 58 Partial for spray−30 −2−1012123spray 456 Figure14: termplot() aov . ( y=β1x+β2x2+α, y~x+x^2).,, y~poly(x,2) , . +Error(b) ,aov() a . ,y~a b . 5.3 ,R \"aov\" ,lm . .R\"lm\" . (,aov ). , . ( ), (generic)18.Rsummary. \"lm\"(. ) \"aov\" 19. , . 20. R 21 . 18 :Java,C++.,R19 :Java 20 :. 21 R100 , . , , Java . . . 59 . : >mod<-lm(y~x)>df.residual(mod)[1]8 printsummary df.residualcoef residualsdeviancefittedlogLikAIC ( ) Akaike (Akaikeinformationcriterion,AIC)( logLik()) aov lm: . InsectSprays , aov >str(aov.spray,max.level=-1)Listof13 -attr(*,\"class\")=chr[1:2]\"aov\"\"lm\" : >names(aov.spray)[1]\"coefficients\"[4]\"rank\"[7]\"qr\" [10]\"xlevels\" \"residuals\" \"fitted.values\"\"df.residual\"\"call\" : \"effects\"\"assign\"\"contrasts\" \"terms\"[13]\"model\" >aov.spray$coefficients(Intercept)sprayBsprayC3.76067840.1159530-2.5158217 sprayEsprayF-1.95121740.2579388 sprayD -1.5963245 aov() summary() : 60 >str(summary(aov.spray))Listof1 $:Classesanovaand‘data.frame’:2obs.of5variables:..$Df:num[1:2]566 ..$SumSq:num[1:2]88.426.1 ..$MeanSq:num[1:2]17.6880.395..$Fvalue:num[1:2]44.8NA..$Pr(>F):num[1:2]0NA -attr(*,\"class\")=chr[1:2]\"summary.aov\"\"listof\">names(summary(aov.spray))NULL : . R , generic.cls, : cls (method).,.,summary , >apropos(\"^summary\") [1]\"summary\"\"summary.aov\"[3]\"summary.aovlist\"\"summary.connection\"[5]\"summary.data.frame\"\"summary.default\"[7]\"summary.factor\"\"summary.glm\"[9]\"summary.glm.null\"\"summary.infl\"[11]\"summary.lm\"\"summary.lm.null\"[13]\"summary.manova\"\"summary.matrix\"[15]\"summary.mlm\" \"summary.packageStatus\"[17]\"summary.POSIXct\"\"summary.POSIXlt\"[19]\"summary.table\" , : >x<-y<-rnorm(5);>lm.spray<-lm(y~x)>names(lm.spray) [1]\"coefficients\"\"residuals\"[4]\"rank\"\"fitted.values\"[7]\"qr\"\"df.residual\"[10]\"call\"\"terms\">names(summary(lm.spray))[1]\"call\"\"terms\"[4]\"coefficients\"\"sigma\" 61 \"effects\"\"assign\"\"xlevels\"\"model\"\"residuals\"\"df\" [7]\"r.squared\"[10]\"cov.unscaled\" \"adj.r.squared\"\"fstatistic\" , update , , predict . add1drop1stepanovapredictupdate AIC( add1 drop1) / , alias , , plot , ( ), . termplotpredict. 5.4 R . R ; search : >search() [1]\".GlobalEnv\"\"package:methods\"[3]\"package:stats\"\"package:graphics\"[5]\"package:grDevices\"\"package:utils\"[7]\"package:datasets\"\"Autoloads\"[9]\"package:base\" : >library(grid) : >library(help=grid) . (7) . 62 basedatasetsgrDevicesgraphicsgridmethodssplinesstatsstats4tcltktoolsutils RR R RR S4 Tcl/Tk R . R. CRAN 22 . , . R . . bootclassclusterforeignKernSmoothlatticeMASSmgcvnlmennetrpartspatialsurvival 22 bootstraping (S3,Stata,SAS,Minitab,SPSS,EpiInfo)( ) Venables&Ripley , “ModernAppliedStatisticswithS” , (“kriging”, ,...) http://cran.r-project.org/src/contrib/PACKAGES.html 63 R :Omegahat 23 R ( ,Bioconductor). CRAN“Packages” 24 ) ( R ., .Windows,Rgui.exe . R,( .gee, 4.13-6;CRAN, (R): , ‘.tar.gz’ gee4.13-6.tar.gz )., RCMDINSTALLgee_4.13-6.tar.gz , installed. download.packages. packages,CRAN.packages, : >update.packages() , “Packages”. CRAN ). (Windows 2324 http://www.omegahat.org/R/http://www.bioconductor.org/ 64 6R , . R , R . 6.1 ,R . , R . x, , x 1. ,Rb C . , 0 y x y: y<-numeric(length(x))for(iin1:length(x))if(x[i]==b)y[i]<-0elsey[i]<-1 : for(iin1:length(x)){ y[i]<-0...} if(x[i]==b){ y[i]<-0...} : while(myfun>minimum){ ...} , R , : . , . , : 65 >z<-x+y , : >z<-numeric(length(x)) >for(iin1:length(z))z[i]<-x[i]+y[i] , , z. , x y : , 25. (if...else) ; : >y[x==b]<-0>y[x!=b]<-1 , , . ‘apply’ X,FUN26),... /,,MARGIN (FUN (1) .apply apply(X,MARGIN,FUN,...), (2),(c(1,2)) , . . > >>> x<-rnorm(10,-5,0.1)y<-rnorm(10,5,2) XX<-cbind(x,y)# apply(X,2,mean) xy -4.9751324.932979>apply(X,2,sd) xy 0.07551532.1388071 \"x\" \"y\" lapply(). : apply >forms<-list(y~x,y~poly(x,2))>lapply(forms,lm)[[1]] :R: withinbrackets” 2526 , ,. “oranoperator,butinthiscaseitmustbespecified 66 Call:FUN(formula=X[[1]])Coefficients:(Intercept) x 31.6835.377 [[2]] Call:FUN(formula=X[[2]])Coefficients:(Intercept)poly(x,2)1 poly(x,2)2 4.93301.2181 -0.6037 sapply() lapply() , , , 6.2 R , R ASCII , ‘.R’. , R . , R . , , layout(matrix(1:3,3,1)) #data<-read.table(\"Swal.dat\")#plot(data$V1,data$V2,type=\"l\")title(\"swallow\") # data<-read.table(\"Wren.dat\")plot(data$V1,data$V2,type=\"l\")title(\"wren\") data<-read.table(\"Dunn.dat\")plot(data$V1,data$V2,type=\"l\")title(\"dunnock\") ‘#’ :R. , , , , . 67 . , .. . ,. layout(matrix(1:3,3,1))#species<-c(\"swallow\\"wren\\"dunnock\") file<-c(\"Swal.dat\",\"Wren.dat\\"Dunn.dat\")for(iin1:length(species)){ data<-read.table(file[i])#plot(data$V1,data$V2,type=\"l\")title(species[i])#} read.table(). .. ‘.dat’ , data/Swal.dat\"). : file[i] , , R , (:file<-\"/home/paradis/Mybirds.R, , >source(\"Mybirds.R\") , , . 6.3 R , . , R . , R. . , : myfun<-function(S,F){data<-read.table(F) plot(data$V1,data$V2,type=\"l\")title(S)} , . , . , , . , source() . 68 R ,, .RData.fordetails).”). , ‘.Rprofile’ , ‘Rprofile’( ( ?Startup“R , , myfun(\"swallow\\"Swal.dat\")., : layout(matrix(1:3,3,1))myfun(\"swallow\\"Swal.dat\")myfun(\"wren\\"Wrenn.dat\")myfun(\"dunnock\\"Dunn.dat\") sapply() : layout(matrix(1:3,3,1)) species<-c(\"swallow\\"wren\\"dunnock\") file<-c(\"Swal.dat\",\"Wren.dat\\"Dunn.dat\")sapply(species,myfun,file) R , . R . , >foo<-function()print(x)>x<-1>foo()[1]1 x foo() , R x , ( x , . >x<-1 >foo2<-function(){x<-2;print(x)}>foo2()[1]2>x[1]1 69 , : , ). x ,print() “”foofoo2 x, foo2 x.: .. , , . : ( ). , : foo<-function(arg1,arg2,arg3){...}arg1,...,foo() ,:foo(x,y,z)., , foo(arg3=z,arg2=y,arg1=x).R .: foo<-function(arg1,arg2=5,arg3=FALSE){...} foo(x),foo(x,5,FALSE) foo(x,arg3=FALSE) . , foo(x,arg3=TRUE) ., .,R . Ricker : Nt+1 =Ntexpr1− Nt K ,.rN0( K1 ) ; . ( ). Ricker . ricker<-function(nzero,r,K=1,time=100,from=0,to=time){ N<-numeric(time+1)N[1]<-nzero for(iin1:time)N[i+1]<-N[i]*exp(r*(1-N[i]/K))Time<-0:time plot(Time,N,type=\"l\xlim=c(from,to))} : >layout(matrix(1:3,3,1)) >ricker(0.1,1);title(\"r=1\")>ricker(0.1,2);title(\"r=2\")>ricker(0.1,3);title(\"r=3\") 70 : , , 7R . RHOME/doc/manual/ R : •R27 [R-intro.pdf], •R [R-admin.pdf], •R/ [R-data.pdf],•R [R-exts.pdf],•R [R-lang.pdf]. (pdf,html,texi,...) . FAQ. RHOME/doc/html/FAQ( AskedQuestions).R-FAQ CRAN http://cran.r-project.org/doc/FAQ/R-FAQ.html .CRAN , R ( ) 29. .R ;, :http://www.R-project.org/mail.html. ‘r-help’. R , ( ). ., , : 1.( ); 2.R-FAQ;3.‘r-help’ , 4. “ ”31. 2728 :.google. http://www.R-project.org/doc/bib/R-publications.html29 http://cran.r-project.org/other-docs.html30 31 http://cran.r-project.org/search.html http://www.r-project.org/posting-guide.html 71 , ,Frequently : R .28 R ‘r-help’ R ‘r-help’ 30; R . .: RNews2001 , 32. R. R, RDevelopmentCoreTeam(2005).R:Alanguageandenvi-ronmentforstatisticalcomputing.RFoundationforStatisti-calComputing,Vienna,Austria.ISBN3-900051-07-0,URL: http://www.R-project.org. 32 http://cran.r-project.org/doc/Rnews/ 72 因篇幅问题不能全部显示，请点此查看更多更全内容