ch1-R软件基本操作

R软件基本操作R软件和软件包安装数学运算向量运算矩阵运算列表、数据框概率函数软件安装(Windows)当前版本3.2.2。至，点击左边download下链接CRAN

，任意选择一个镜像站点，比如USA下http://r.B

。在DownloadandInstallR中选择DownloadRforWindows

，点击base，选择文件DownloadR3.2.2forWindows

，点击鼠标右键另存为保存到指定目录中。下载好后安装R。软件包安装比如安装“BRugs”，可以使用命令>install.packages("BRugs",repos="http://r.B",dep=TRUE)调用软件包

>require(BRugs)#>library(BRugs)升级软件包>update.packages(repos="http://r.B",dep=TRUE)删除软件包

>remove.packages("BRugs",lib=file.path("path","to","library"))命令的执行主窗口REditor窗口(File-Newscript)require(Rcmdr)常用的小技巧查看工作目录：>getwd()[1]"D:/ProgramFiles/R/R-2.11.1”设定工作目录：>setwd("d:/ProgramFiles/R")>getwd()[1]"d:/ProgramFiles/R”取得帮助：>help.start()#打开帮助文档>help.search('paneldata')>RSiteSearch('KalmanFilter')>?lm查看对象类型：>typeof()>class()单引号和双引号的区别：>c("single'qutoe",'double"quote',"double\"quote",'single\'quote')[1]"single'qutoe""double\"quote""double\"quote""single'quote"更改选项设定>

options(prompt='R>',continue='R')运算符号+-*/^<<=>>===!=%%余数%/%商%in%判断>17%in%1:100[1]TRUE基本数学运算加减乘除乘方运算>5+6*7/12^(1/3)[1]23.34519指数对数运算>exp(2)#e^2[1]7.389056>log(2,10)#lg(2)[1]0.30103>log(exp(1))#ln(e)[1]1基本数学运算（续）求导>D(expression(x^2),"x")2*x>D(expression(sin(x^2)),"x")cos(x^2)*(2*x)积分：利用函数integrate()>integrate(dnorm,-1.96,1.96)$value[1]0.9500042>integrate(dnorm,-Inf,Inf)$value[1]1#对于多重积分计算，利用adapt库中函数adapt，不允许用无穷界限。f<-function(x){1/sqrt(2*pi)*exp(-x^2/2)}integrate(f,-1.96,1.96)$value复数运算‘Re’-实部‘Im’-虚部‘Mod’-模‘Arg’-角度‘Conj’-共轭

r=Mod(z)=√(x^2+y^2),φ=Arg(z),x=r*cos(φ)

y=r*sin(φ)

解方程(组)>polyroot(c(-3,2,1))[1]1+0i-3-0i>A<-matrix(c(2,3,1,1),ncol=2,byrow=T)>A[,1][,2][1,]23[2,]11>B<-c(1,-1)>solve(A,B)[1]-43x^2+2x-3=02x+3y=1x+y=-1集合运算并>union(x,y)交>intersect(x,y)补>setdiff(x,y)>x<-1:20>y<-3:15>intersect(x,y)[1]3456789101112131415>union(x,y)[1]1234567891011121314151617181920>match(y,x)[1]3456789101112131415>z<-c(23,15,12)>match(y,z)[1]NANA

NA

NA

NA

NA

NA

NA

NA3NANA2>setdiff(x,y)#从x中消去y[1]121617181920排列组合choose(n,k)-组合数combn(n,k)-列出所有组合factorial(n)-阶乘require(e1071)>permutations(3)[,1][,2][,3][1,]123[2,]213[3,]231[4,]132[5,]312[6,]321序列和向量

z<-seq(-1,10,length=100)#z<-seq(-1,10,len=100)z<-seq(10,-1,-1)#z<-10:-1>x<-rep(3,1:3)Errorinrep(3,1:3):invalid'times'argumentx<-rep(3:5,1:3)>x[1]344555x<-rep(c(1,10),c(4,5))w<-c(1,3,x,z);w[3]向量运算

x<-rep(0,10);z<-1:3;x+z

[1]1231231231Warningmessage:longerobjectlengthisnotamultipleofshorterobjectlengthin:x+z

x*z[1]0000000000Warningmessage:longerobjectlengthisnotamultipleofshorterobjectlengthin:x*zrev(x)z<-

c("no

cat","has","nine","tails")z[1]=="nocat"[1]TRUE向量名和元素附加

x<-1:3;names(x)<-LETTERS[1:3]xABC123set.seed(10);append(x,runif(3),after=2)

ABC1.00002.00000.50750.30680.42693.0000向量赋值

z<-1:5z[7]<-8;z[1]12345NA8z<-NULLz[c(1,3,5)]<-1:3;z[1]1NA2NA3rnorm(10)[c(2,5)]z[-c(1,3)]#去掉第1、3元素.z[(length(z)-4):length(z)]#最后五个元素.向量的大小次序

set.seed(10);z<-sample(1:100,10);z

#比较sample(1:100,10,rep=T)

[1]5131426892226945740

order(z)#给出数据从小到大的位置，即最小的是第5个

[1]56721031948z[order(z)]

[1]9222631404251576894sort(z)

[1]9222631404251576894which(z==max(z))#给出下标[1]8矩阵操作>(A<-matrix(1:12,3,4))[,1][,2][,3][,4][1,]14710[2,]25811[3,]36912>(A<-matrix(1:12,3,4,byrow=T))

[,1][,2][,3][,4][1,]1234[2,]5678[3,]9101112>dim(A)[1]34矩阵操作(续)>nrow(A)[1]3>dim(A)[1][1]3>ncol(A)[1]4>dim(A)[2][1]4>A[3,][1]9101112>A[,3][1]3711>A[3,3][1]11矩阵操作(续)>A[-1,]#去除A的第一行

[,1][,2][,3][,4][1,]5678[2,]9101112>A[,-2]#去除A的第二列[,1][,2][,3][1,]134[2,]578[3,]91112>(AA<-matrix(1:9,3,3))[,1][,2][,3][1,]147[2,]258[3,]369>AA[-2,-2]#删除AA矩阵的第二行第二列

[,1][,2][1,]17[2,]39矩阵操作(续)>A>3#判断A中元素是否大于3

[,1][,2][,3][,4][1,]FALSEFALSEFALSETRUE[2,]TRUETRUETRUETRUE[3,]TRUETRUE

TRUE

TRUE>A==3

[,1][,2][,3][,4][1,]FALSEFALSETRUEFALSE[2,]FALSEFALSEFALSEFALSE[3,]FALSEFALSEFALSEFALSE>A[A>6][1]910711812>length(A[A>6])[1]6矩阵操作(续)>(A<-matrix(0,3,3))[,1][,2][,3][1,]000[2,]000[3,]000>diag(A)<-1>diag(A)[1]111>diag(1,3,3)

[,1][,2][,3][1,]100[2,]010[3,]001矩阵操作(续)>(m2<-matrix(1:20,4,5))[,1][,2][,3][,4][,5][1,]1591317[2,]26101418[3,]37111519[4,]48121620>lower.tri(m2)[,1][,2][,3][,4][,5][1,]FALSEFALSEFALSEFALSEFALSE[2,]TRUEFALSEFALSEFALSEFALSE[3,]TRUETRUEFALSEFALSEFALSE[4,]TRUETRUETRUEFALSEFALSE>m2[lower.tri(m2)]<-NA>m2

[,1][,2][,3][,4][,5][1,]1591317[2,]NA6101418[3,]NANA111519[4,]NANA

NA1620矩阵加减>(A<-matrix(1:12,3,4))[,1][,2][,3][,4][1,]14710[2,]25811[3,]36912>(B<-matrix(-1:-12,3,4))[,1][,2][,3][,4][1,]-1-4-7-10[2,]-2-5-8-11[3,]-3-6-9-12>(C1<-A+B)[,1][,2][,3][,4][1,]0000[2,]0000[3,]0000>(D1<-A-B)[,1][,2][,3][,4][1,]281420[2,]4101622[3,]6121824矩阵数乘>(A<-matrix((1:9)^2,3,3))[,1][,2][,3][1,]11649[2,]42564[3,]93681>(AmultipliedByTwo<-2*A)[,1][,2][,3][1,]23298[2,]850128[3,]1872162>(AmultipliedByTwo/2==A)[,1][,2][,3][1,]TRUETRUE

TRUE[2,]TRUETRUETRUE[3,]TRUETRUETRUE矩阵相乘>(E<-matrix(1:9,3,3));(E2<-matrix(1:9,3,3,byrow=T))[,1][,2][,3][1,]147[2,]258[3,]369[,1][,2][,3][1,]123[2,]456[3,]789>E2%*%E[,1][,2][,3][1,]143250[2,]3277122[3,]50122194矩阵逆>(B<-matrix((1:9)^2,3,3))[,1][,2][,3][1,]11649[2,]42564[3,]93681>(Binverse<-solve(B))

[,1][,2][,3][1,]1.291667-2.1666670.9305556[2,]-1.1666671.666667-0.6111111[3,]0.375000-0.5000000.1805556>B%*%Binverse[,1][,2][,3][1,]1.000000e+00-8.881784e-169.714451e-16[2,]-3.552714e-151.000000e+000.000000e+00[3,]6.661338e-16-8.881784e-161.000000e+00>round(B%*%Binverse)[,1][,2][,3][1,]100[2,]010[3,]001矩阵分解因子分解（谱（spectral）分解）>J<-cbind(c(20,3),c(3,18))>j<-eigen(J,symmetric=T)>j$values[1]22.1622815.83772$vectors[,1][,2][1,]-0.81124220.5847103[2,]-0.5847103-0.8112422>C<-j$vec>D<-diag(j$values)>C%*%D%*%t(C)[,1][,2][1,]203[2,]318

C是特征向量构成的列矩阵，是特征值构成的对角阵。矩阵分解(续)奇异值（singularvalue）分解

>H<-matrix(c(3,2,1,1,1,2),3,2)>(HHt.eigen=eigen(H%*%t(H)))$values[1]1.806226e+011.937742e+002.153937e-15$vectors[,1][,2][,3][1,]0.7286301-0.460386080.5070926[2,]0.5251205-0.09981375-0.8451543[3,]0.43971210.882089490.1690309>U=HHt.eigen$vec[,1:2]>D=diag(sqrt(HHt.eigen$val)[1:2])>V=t(H)%*%U%*%solve(D)>U%*%D%*%t(V)或>svd(H)的特征向量矩阵为，的对角元素是的非零特征值的平方根

矩阵分解(续)Cholesky分解，实对称正定矩阵的分解>A<-matrix(c(1,2,2,5),ncol=2)>A>H<-chol(A)>H>t(H)%*%H为非奇异阵，上三角阵列表list可以是任何对象的集合(包括lists)z<-list(1:3,Tom=c(1:2,a=list("R",letters[1:5]),w="hi!"))z[[1]];z[[2]];z$T;z$T$a2;z$T[[3]];z$T$wattributes(z)#属性!$names[1]"""Tom"attributes(matrix(1:6,2,3))$dim[1]23矩阵,数组及其维名字

x<-matrix(1:12,nrow=3,dimnames=list(c("I","II","III"),paste("X",1:4,sep="")))

X1X2X3X4I14710II25811III36912y<-array(1:12,c(3,2,2),dimnames=list(c("I","II","III"),paste("X",1:2,sep=""),paste("Y",1:2,sep=""))),,Y1X1X2I14II25III36,,Y2X1X2I710II811III912数据框

x<-matrix(1:6,2,3)x<-

as.data.frame(x);xV1V2V311352246x$V2[1]34x$V2[1]34attributes(x)$names[1]"V1""V2""V3"$s[1]"1""2"$class[1]"data.frame"数据框(续