(QQ图实例R软件.docVIP

rm(list=ls()) DA=read.csv(file=file.choose(),head=T) lm.reg=lm(DA$Y~X1+X2+X3+X4+X5+X6+X7+X8+X9+X10+X11+X12+X13+X14+X15+X16+X17+X18+X19+X20+X21+X22+X23+X24+X25+X26+X27+X28+X29+X30+X31+X32+X33+X34+X35+X36+X37+X38+X39+X40+X41+X42+X43+X44+X45+X46+X47+X48+X49+X50,data=DA) summary(lm.reg) plot(lm.reg,2) XX-cor(DA[1:50]) kappa(XX,exact=TRUE) eigen(XX) p=1 n=nrow(DA) d1=dffits(lm.reg) Y=1:n Y[abs(d1)2*sqrt((p+1)/n)] infl=lm.influence(lm.reg,do.coef=FALSE) D=cooks.distance(lm.reg,infl=lm.influence(lm.reg,do.coef=FALSE), + rs=weighted.residuals(lm.reg), + sd=sqrt(deviance(lm.reg)/df.residual(lm.reg)), + hat=infl$hat) sort(D) D=abs(1-covratio(lm.reg, infl=lm.influence(lm.reg, do.coef = FALSE),res = + weighted.residuals(lm.reg))) sort(D) Reg_Diag-function(fm){ + n-nrow(fm$model); df-fm$df.residual + p-n-df-1; s-rep( , n); + res-residuals(fm); s1-s; s1[abs(res)==max(abs(res))]-* + sta-rstandard(fm); s2-s; s2[abs(sta)2]-* + stu-rstudent(fm); s3-s; s3[abs(sta)2]-* + h-hatvalues(fm); s4-s; s4[h2*(p+1)/n]-* + d-dffits(fm); s5-s; s5[abs(d)2*sqrt((p+1)/n)]-* + c-cooks.distance(fm); s6-s; s6[c==max(c)]-* + co-covratio(fm); abs_co-abs(co-1) + s7-s; s7[abs_co==max(abs_co)]-* + data.frame(residual=res, s1, standard=sta, s2, + student=stu, s3, hat_matrix=h, s4, + DFFITS=d, s5,cooks_distance=c, s6, + COVRATIO=co, s7)} Reg_Diag(lm.reg)