W3_Mini_1 | ||||||||||||||||||||||||||||||
| *The author of this computation has been verified* | ||||||||||||||||||||||||||||||
| R Software Module: /rwasp_linear_regression.wasp (opens new window with default values) | ||||||||||||||||||||||||||||||
| Title produced by software: Linear Regression Graphical Model Validation | ||||||||||||||||||||||||||||||
| Date of computation: Wed, 24 Nov 2010 18:41:50 +0000 | ||||||||||||||||||||||||||||||
| Cite this page as follows: | ||||||||||||||||||||||||||||||
| Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Nov/24/t1290624079cf21z3cmbdays88.htm/, Retrieved Wed, 24 Nov 2010 19:41:28 +0100 | ||||||||||||||||||||||||||||||
| BibTeX entries for LaTeX users: | ||||||||||||||||||||||||||||||
@Manual{KEY,
author = {{YOUR NAME}},
publisher = {Office for Research Development and Education},
title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Nov/24/t1290624079cf21z3cmbdays88.htm/},
year = {2010},
}
@Manual{R,
title = {R: A Language and Environment for Statistical Computing},
author = {{R Development Core Team}},
organization = {R Foundation for Statistical Computing},
address = {Vienna, Austria},
year = {2010},
note = {{ISBN} 3-900051-07-0},
url = {http://www.R-project.org},
}
| ||||||||||||||||||||||||||||||
| Original text written by user: | ||||||||||||||||||||||||||||||
| IsPrivate? | ||||||||||||||||||||||||||||||
| No (this computation is public) | ||||||||||||||||||||||||||||||
| User-defined keywords: | ||||||||||||||||||||||||||||||
| Dataseries X: | ||||||||||||||||||||||||||||||
| » Textbox « » Textfile « » CSV « | ||||||||||||||||||||||||||||||
| 276444 289742 303725 298305 266795 259497 266148 271037 276239 279681 277509 271115 275902 287224 300713 293860 264221 256167 262572 263276 264291 263903 260376 255603 261076 270976 285257 280445 250741 243803 253158 255542 262522 268381 267153 266424 276427 286994 303598 296806 263290 264981 272566 276475 284678 291542 291413 295916 309119 327616 | ||||||||||||||||||||||||||||||
| Dataseries Y: | ||||||||||||||||||||||||||||||
| » Textbox « » Textfile « » CSV « | ||||||||||||||||||||||||||||||
| 563668 586111 604378 600991 544686 537034 551531 563250 574761 580112 575093 557560 564478 580523 596594 586570 536214 523597 536535 536322 532638 528222 516141 501866 506174 517945 533590 528379 477580 469357 490243 492622 507561 516922 514258 509846 527070 541657 564591 555362 498662 511038 525919 531673 548854 560576 557274 565742 587625 619916 | ||||||||||||||||||||||||||||||
| Output produced by software: | ||||||||||||||||||||||||||||||
| ||||||||||||||||||||||||||||||
| Charts produced by software: | ||||||||||||||||||||||||||||||
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| Parameters (Session): | ||||||||||||||||||||||||||||||
| par1 = 0 ; | ||||||||||||||||||||||||||||||
| Parameters (R input): | ||||||||||||||||||||||||||||||
| par1 = 0 ; | ||||||||||||||||||||||||||||||
| R code (references can be found in the software module): | ||||||||||||||||||||||||||||||
| par1 <- as.numeric(par1)
library(lattice) z <- as.data.frame(cbind(x,y)) m <- lm(y~x) summary(m) bitmap(file='test1.png') plot(z,main='Scatterplot, lowess, and regression line') lines(lowess(z),col='red') abline(m) grid() dev.off() bitmap(file='test2.png') m2 <- lm(m$fitted.values ~ x) summary(m2) z2 <- as.data.frame(cbind(x,m$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() bitmap(file='test3.png') m3 <- lm(m$residuals ~ x) summary(m3) z3 <- as.data.frame(cbind(x,m$residuals)) names(z3) <- list('x','Residuals') plot(z3,main='Scatterplot, lowess, and regression line') lines(lowess(z3),col='red') abline(m3) grid() dev.off() bitmap(file='test4.png') m4 <- lm(m$fitted.values ~ m$residuals) summary(m4) 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() bitmap(file='test5.png') myr <- as.ts(m$residuals) z5 <- as.data.frame(cbind(lag(myr,1),myr)) names(z5) <- list('Lagged Residuals','Residuals') plot(z5,main='Lag plot') m5 <- lm(z5) summary(m5) abline(m5) grid() dev.off() bitmap(file='test6.png') hist(m$residuals,main='Residual Histogram',xlab='Residuals') dev.off() bitmap(file='test7.png') 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() bitmap(file='test8.png') acf(m$residuals,main='Residual Autocorrelation Function') dev.off() bitmap(file='test9.png') qqnorm(x) qqline(x) grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Simple Linear Regression',5,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Statistics',1,TRUE) a<-table.element(a,'Estimate',1,TRUE) a<-table.element(a,'S.D.',1,TRUE) a<-table.element(a,'T-STAT (H0: coeff=0)',1,TRUE) a<-table.element(a,'P-value (two-sided)',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'constant term',header=TRUE) a<-table.element(a,m$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='mytable.tab') | ||||||||||||||||||||||||||||||
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