R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> y <- c(1.2999,1.3074,1.3242,1.3516,1.3511,1.3419,1.3716,1.3622,1.3896,1.4227,1.4684,1.457,1.4718,1.4748,1.5527,1.575,1.5557,1.5553,1.577,1.4975,1.4369,1.3322,1.2732,1.3449,1.3239,1.2785,1.305,1.319,1.365,1.4016,1.4088,1.4268,1.4562,1.4816,1.4914,1.4614,1.4272,1.3686,1.3569,1.3406,1.2565,1.2208,1.277,1.2894,1.3067,1.3898,1.3661,1.322,1.336,1.3649,1.3999,1.4442,1.4349,1.4388,1.4264,1.4343,1.377,1.3706,1.3556,1.3179,1.2905,1.3224,1.3201,1.3162,1.2789,1.2526,1.2288,1.24,1.2856,1.2974)
> x <- c(31/01/2007,28/02/2007,31/03/2007,30/04/2007,31/05/2007,30/06/2007,31/07/2007,31/08/2007,30/09/2007,31/10/2007,30/11/2007,31/12/2007,31/01/2008,29/02/2008,31/03/2008,30/04/2008,31/05/2008,30/06/2008,31/07/2008,31/08/2008,30/09/2008,31/10/2008,30/11/2008,31/12/2008,31/01/2009,28/02/2009,31/03/2009,30/04/2009,31/05/2009,30/06/2009,31/07/2009,31/08/2009,30/09/2009,31/10/2009,30/11/2009,31/12/2009,31/01/2010,28/02/2010,31/03/2010,30/04/2010,31/05/2010,30/06/2010,31/07/2010,31/08/2010,30/09/2010,31/10/2010,30/11/2010,31/12/2010,31/01/2011,28/02/2011,31/03/2011,30/04/2011,31/05/2011,30/06/2011,31/07/2011,31/08/2011,30/09/2011,31/10/2011,30/11/2011,31/12/2011,31/01/2012,29/02/2012,31/03/2012,30/04/2012,31/05/2012,30/06/2012,31/07/2012,31/08/2012,30/09/2012,31/10/2012)
> par1 = '0'
> par1 <- '0'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P., (2012), Linear Regression Graphical Model Validation (v1.0.7) 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
> #
> 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 
-0.15723 -0.05922 -0.01512  0.05781  0.19928 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)   1.3826     0.0148  93.419   <2e-16 ***
x            -1.8534     2.6629  -0.696    0.489    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.08638 on 68 degrees of freedom
Multiple R-squared: 0.007074,	Adjusted R-squared: -0.007528 
F-statistic: 0.4844 on 1 and 68 DF,  p-value: 0.4888 

> postscript(file="/var/fisher/rcomp/tmp/1cklk1353441875.ps",horizontal=F,onefile=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/fisher/rcomp/tmp/266ae1353441875.ps",horizontal=F,onefile=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 
-1.229e-16 -5.900e-17  2.497e-18  4.481e-17  2.504e-16 

Coefficients:
              Estimate Std. Error    t value Pr(>|t|)    
(Intercept)  1.383e+00  1.209e-17  1.143e+17   <2e-16 ***
x           -1.853e+00  2.176e-15 -8.519e+14   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 7.057e-17 on 68 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 7.258e+29 on 1 and 68 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/3vwao1353441875.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-0.15723 -0.05922 -0.01512  0.05781  0.19928 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)  3.838e-18  1.480e-02       0        1
x           -2.115e-16  2.663e+00       0        1

Residual standard error: 0.08638 on 68 degrees of freedom
Multiple R-squared: 9.023e-34,	Adjusted R-squared: -0.01471 
F-statistic: 6.136e-32 on 1 and 68 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/4z75y1353441875.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
      Min        1Q    Median        3Q       Max 
-0.021247 -0.001490  0.002774  0.004308  0.005000 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  1.375e+00  8.714e-04    1578   <2e-16 ***
m$residuals -1.081e-16  1.024e-02       0        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.007291 on 68 degrees of freedom
Multiple R-squared:     0,	Adjusted R-squared: -0.01471 
F-statistic:     0 on 1 and 68 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/fisher/rcomp/tmp/5zbwt1353441875.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> myr <- as.ts(m$residuals)
> z5 <- as.data.frame(cbind(lag(myr,1),myr))
> names(z5) <- list('Lagged Residuals','Residuals')
> plot(z5,main='Lag plot')
> m5 <- lm(z5)
> summary(m5)

Call:
lm(formula = z5)

Residuals:
      Min        1Q    Median        3Q       Max 
-0.099236 -0.015908  0.002193  0.026079  0.084259 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept) -0.0002977  0.0044970  -0.066    0.947    
Residuals    0.9061277  0.0527957  17.163   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.03735 on 67 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.8147,	Adjusted R-squared: 0.8119 
F-statistic: 294.6 on 1 and 67 DF,  p-value: < 2.2e-16 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/64m361353441875.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/7gtdl1353441875.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/8bvfg1353441875.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/9bc2u1353441875.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> qqnorm(x)
> qqline(x)
> grid()
> dev.off()
null device 
          1 
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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/fisher/rcomp/tmp/10ae8q1353441875.tab") 
> 
> try(system("convert tmp/1cklk1353441875.ps tmp/1cklk1353441875.png",intern=TRUE))
character(0)
> try(system("convert tmp/266ae1353441875.ps tmp/266ae1353441875.png",intern=TRUE))
character(0)
> try(system("convert tmp/3vwao1353441875.ps tmp/3vwao1353441875.png",intern=TRUE))
character(0)
> try(system("convert tmp/4z75y1353441875.ps tmp/4z75y1353441875.png",intern=TRUE))
character(0)
> try(system("convert tmp/5zbwt1353441875.ps tmp/5zbwt1353441875.png",intern=TRUE))
character(0)
> try(system("convert tmp/64m361353441875.ps tmp/64m361353441875.png",intern=TRUE))
character(0)
> try(system("convert tmp/7gtdl1353441875.ps tmp/7gtdl1353441875.png",intern=TRUE))
character(0)
> try(system("convert tmp/8bvfg1353441875.ps tmp/8bvfg1353441875.png",intern=TRUE))
character(0)
> try(system("convert tmp/9bc2u1353441875.ps tmp/9bc2u1353441875.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  5.434   1.213   6.653