R version 2.6.1 (2007-11-26)
Copyright (C) 2007 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> y <- c(50,20,10,50,30,50,70,20,30,10,50)
> x <- c(80,60,10,20,30,10,10,50,80,90,30)
> par1 = '0'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: Wessa P., (2007), Linear Regression Graphical Model Validation (v1.0.2) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_linear_regression.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description
> par1 <- as.numeric(par1)
> library(lattice)
> z <- as.data.frame(cbind(x,y))
> m <- lm(y~x)
> summary(m)

Call:
lm(formula = y ~ x)

Residuals:
    Min      1Q  Median      3Q     Max 
-34.015 -12.013   4.295   9.908  25.985 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)   
(Intercept)  46.6313    10.1064   4.614  0.00127 **
x            -0.2616     0.1952  -1.340  0.21297   
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 18.94 on 9 degrees of freedom
Multiple R-Squared: 0.1664,	Adjusted R-squared: 0.07378 
F-statistic: 1.797 on 1 and 9 DF,  p-value: 0.2130 

> postscript(file="/var/www/html/rcomp/tmp/1dkni1201526841.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(z,main='Scatterplot, lowess, and regression line')
> lines(lowess(z),col='red')
> abline(m)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/20qdk1201526841.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m2 <- lm(m$fitted.values ~ x)
> summary(m2)

Call:
lm(formula = m$fitted.values ~ x)

Residuals:
       Min         1Q     Median         3Q        Max 
-7.893e-15 -6.064e-15  2.747e-16  2.343e-15  2.096e-14 

Coefficients:
              Estimate Std. Error    t value Pr(>|t|)    
(Intercept)  4.663e+01  4.612e-15  1.011e+16   <2e-16 ***
x           -2.616e-01  8.905e-17 -2.937e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 8.642e-15 on 9 degrees of freedom
Multiple R-Squared:     1,	Adjusted R-squared:     1 
F-statistic: 8.628e+30 on 1 and 9 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/3bfg11201526841.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

Call:
lm(formula = m$residuals ~ x)

Residuals:
    Min      1Q  Median      3Q     Max 
-34.015 -12.013   4.295   9.908  25.985 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)
(Intercept)  4.930e-16  1.011e+01  4.88e-17        1
x           -3.661e-17  1.952e-01 -1.88e-16        1

Residual standard error: 18.94 on 9 degrees of freedom
Multiple R-Squared: 2.288e-32,	Adjusted R-squared: -0.1111 
F-statistic: 2.059e-31 on 1 and 9 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/4rvbn1201526841.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

Call:
lm(formula = m$fitted.values ~ m$residuals)

Residuals:
    Min      1Q  Median      3Q     Max 
-12.366  -7.134   3.329   7.253   8.561 

Coefficients:
             Estimate Std. Error  t value Pr(>|t|)    
(Intercept) 3.545e+01  2.551e+00    13.90 2.19e-07 ***
m$residuals 1.720e-16  1.489e-01 1.15e-15        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 8.462 on 9 degrees of freedom
Multiple R-Squared: 5.484e-31,	Adjusted R-squared: -0.1111 
F-statistic: 4.936e-30 on 1 and 9 DF,  p-value: 1 

> z4 <- as.data.frame(cbind(m$residuals,m$fitted.values))
> names(z4) <- list('Residuals','Fitted')
> plot(z4,main='Scatterplot, lowess, and regression line')
> lines(lowess(z4),col='red')
> abline(m4)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/58bke1201526841.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> myr <- as.ts(m$residuals)
> m5 <- lm(myr ~ lag(myr,1))
> summary(m5)

Call:
lm(formula = myr ~ lag(myr, 1))

Residuals:
       Min         1Q     Median         3Q        Max 
-5.549e-15 -3.039e-15 -8.279e-16 -1.659e-16  1.676e-14 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)    
(Intercept) -7.136e-31  1.875e-15 -3.81e-16        1    
lag(myr, 1)  1.000e+00  1.095e-16 9.136e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 6.219e-15 on 9 degrees of freedom
Multiple R-Squared:     1,	Adjusted R-squared:     1 
F-statistic: 8.347e+31 on 1 and 9 DF,  p-value: < 2.2e-16 

> z5 <- as.data.frame(cbind(lag(myr,1),myr))
> names(z5) <- list('Lagged Residuals','Residuals')
> plot(z5,main='Lag plot')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/6evdw1201526841.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/72sgq1201526841.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~x,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~x,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/8pt721201526841.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/94g2w1201526841.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> qqnorm(x)
> grid()
> dev.off()
null device 
          1 
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Simple Linear Regression',5,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Statistics',1,TRUE)
> a<-table.element(a,'Estimate',1,TRUE)
> a<-table.element(a,'S.D.',1,TRUE)
> a<-table.element(a,'T-STAT (H0: coeff=0)',1,TRUE)
> a<-table.element(a,'P-value (two-sided)',1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'constant term',header=TRUE)
> a<-table.element(a,m$coefficients[[1]])
> sd <- sqrt(vcov(m)[1,1])
> a<-table.element(a,sd)
> tstat <- m$coefficients[[1]]/sd
> a<-table.element(a,tstat)
> pval <- 2*(1-pt(abs(tstat),length(x)-2))
> a<-table.element(a,pval)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'slope',header=TRUE)
> a<-table.element(a,m$coefficients[[2]])
> sd <- sqrt(vcov(m)[2,2])
> a<-table.element(a,sd)
> tstat <- m$coefficients[[2]]/sd
> a<-table.element(a,tstat)
> pval <- 2*(1-pt(abs(tstat),length(x)-2))
> a<-table.element(a,pval)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/10dl081201526841.tab") 
> 
> system("convert tmp/1dkni1201526841.ps tmp/1dkni1201526841.png")
> system("convert tmp/20qdk1201526841.ps tmp/20qdk1201526841.png")
> system("convert tmp/3bfg11201526841.ps tmp/3bfg11201526841.png")
> system("convert tmp/4rvbn1201526841.ps tmp/4rvbn1201526841.png")
> system("convert tmp/58bke1201526841.ps tmp/58bke1201526841.png")
> system("convert tmp/6evdw1201526841.ps tmp/6evdw1201526841.png")
> system("convert tmp/72sgq1201526841.ps tmp/72sgq1201526841.png")
> system("convert tmp/8pt721201526841.ps tmp/8pt721201526841.png")
> system("convert tmp/94g2w1201526841.ps tmp/94g2w1201526841.png")
> 
> 
> proc.time()
   user  system elapsed 
  2.012   1.338   2.635