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B28A,regression tree,steven,coomans,thesis,per2maand

*Unverified author*

R Software Module: /rwasp_regression_trees.wasp (opens new window with default values)

Title produced by software: Recursive Partitioning (Regression Trees)

Date of computation: Wed, 26 May 2010 11:18:08 +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/May/26/t1274872737alncyl67vx7xnpc.htm/, Retrieved Wed, 26 May 2010 13:18:57 +0200

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/May/26/t1274872737alncyl67vx7xnpc.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:

B28A,regression tree,steven,coomans,thesis,per2maand

Dataseries X:

» Textbox « » Textfile « » CSV «

250.75 NA 250.850152884021 251.27004 336,675 314.5125 250.75 314.369477869004 251.27004 352,25 449.3885 257.12625 448.784077969190 251.27004 392,025 305.7 276.352475 305.685475232751 251.27004 435,275 162.375 279.2872275 162.837106781298 251.27004 148,75 352.025 267.59600475 351.787128034443 251.27004 388,875 379.125 276.038904275 378.830448248692 251.27004 359,65 327.125 286.3475138475 327.047794937283 251.27004 139,9 423.6625 290.42526246275 423.280779333534 251.27004 440,5 152.25 303.748986216475 152.776138996337 251.27004 220,875 183.8125 288.599087594828 184.199992170458 251.27004 234,5 153.8875 278.120428835345 154.348519548268 251.27004 161,9 245.625 265.697135951810 245.711928676033 251.27004 258,25 108.9 263.689922356629 109.490720296634 251.27004 222,5 291.625 248.210930120966 291.441298968799 251.27004 279,35 284.875 252.552337108870 284.744734135499 251.27004 415,8 192.25 255.784603397983 192.499491581822 251.27004 168,9 45.2625 249.431143058184 46.0800968454689 251.27004 67,125 etc...

Output produced by software:

Enter (or paste) a matrix (table) containing all data (time) series. Every column represents a different variable and must be delimited by a space or Tab. Every row represents a period in time (or category) and must be delimited by hard returns. The easiest way to enter data is to copy and paste a block of spreadsheet cells. Please, do not use commas or spaces to seperate groups of digits!

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24
R Framework error message	Warning: there are blank lines in the 'Data X' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.

Model Performance
#	Complexity	split	relative error	CV error	CV S.D.
1	0.703	0	1	1.073	0.258
2	0.01	1	0.297	0.401	0.107

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/May/26/t1274872737alncyl67vx7xnpc/1zagu1274872684.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274872737alncyl67vx7xnpc/1zagu1274872684.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274872737alncyl67vx7xnpc/2s1fx1274872684.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274872737alncyl67vx7xnpc/2s1fx1274872684.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274872737alncyl67vx7xnpc/3s1fx1274872684.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274872737alncyl67vx7xnpc/3s1fx1274872684.ps (open in new window)

Parameters (Session):

par1 = 1 ; par2 = No ;

Parameters (R input):

par1 = 1 ; par2 = No ;

R code (references can be found in the software module):

library(rpart)

library(partykit)

par1 <- as.numeric(par1)

autoprune <- function ( tree, method='Minimum CV'){

xerr <- tree$cptable[,'xerror']

cpmin.id <- which.min(xerr)

if (method == 'Minimum CV Error plus 1 SD'){

xstd <- tree$cptable[,'xstd']

errt <- xerr[cpmin.id] + xstd[cpmin.id]

cpSE1.min <- which.min( errt < xerr )

mycp <- (tree$cptable[,'CP'])[cpSE1.min]

}

if (method == 'Minimum CV') {

mycp <- (tree$cptable[,'CP'])[cpmin.id]

}

return (mycp)

}

conf.multi.mat <- function(true, new)

{

if ( all( is.na(match( levels(true),levels(new) ) )) )

stop ( 'conflict of vector levels')

multi.t <- list()

for (mylev in levels(true) ) {

true.tmp <- true

new.tmp <- new

left.lev <- levels (true.tmp)[- match(mylev,levels(true) ) ]

levels(true.tmp) <- list ( mylev = mylev, all = left.lev )

levels(new.tmp)  <- list ( mylev = mylev, all = left.lev )

curr.t <- conf.mat ( true.tmp , new.tmp )

multi.t[[mylev]] <- curr.t

multi.t[[mylev]]$precision <-

round( curr.t$conf[1,1] / sum( curr.t$conf[1,] ), 2 )

}

return (multi.t)

}

x <- t(y)

k <- length(x[1,])

n <- length(x[,1])

x1 <- cbind(x[,par1], x[,1:k!=par1])

mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])

colnames(x1) <- mycolnames #colnames(x)[par1]

m <- rpart(as.data.frame(x1))

par2

if (par2 != 'No') {

mincp <- autoprune(m,method=par2)

print(mincp)

m <- prune(m,cp=mincp)

}

m$cptable

bitmap(file='test1.png')

plot(as.party(m),tp_args=list(id=FALSE))

dev.off()

bitmap(file='test2.png')

plotcp(m)

dev.off()

cbind(y=m$y,pred=predict(m),res=residuals(m))

myr <- residuals(m)

myp <- predict(m)

bitmap(file='test4.png')

op <- par(mfrow=c(2,2))

plot(myr,ylab='residuals')

plot(density(myr),main='Residual Kernel Density')

plot(myp,myr,xlab='predicted',ylab='residuals',main='Predicted vs Residuals')

plot(density(myp),main='Prediction Kernel Density')

par(op)

dev.off()

load(file='createtable')

a<-table.start()

a<-table.row.start(a)

a<-table.element(a,'Model Performance',6,TRUE)

a<-table.row.end(a)

a<-table.row.start(a)

a<-table.element(a,'#',header=TRUE)

a<-table.element(a,'Complexity',header=TRUE)

a<-table.element(a,'split',header=TRUE)

a<-table.element(a,'relative error',header=TRUE)

a<-table.element(a,'CV error',header=TRUE)

a<-table.element(a,'CV S.D.',header=TRUE)

a<-table.row.end(a)

for (i in 1:length(m$cptable[,1])) {

a<-table.row.start(a)

a<-table.element(a,i,header=TRUE)

a<-table.element(a,round(m$cptable[i,'CP'],3))

a<-table.element(a,m$cptable[i,'nsplit'])

a<-table.element(a,round(m$cptable[i,'rel error'],3))

a<-table.element(a,round(m$cptable[i,'xerror'],3))

a<-table.element(a,round(m$cptable[i,'xstd'],3))

a<-table.row.end(a)

}

a<-table.end(a)

table.save(a,file='mytable.tab')

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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