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FM50,regression tree,steven,coomans,thesis,per maand

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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 10:54:54 +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/t1274871352f8rik8ythou3ogg.htm/, Retrieved Wed, 26 May 2010 12:55:52 +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/t1274871352f8rik8ythou3ogg.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:

FM50,regression tree,steven,coomans,thesis,per maand

Dataseries X:

» Textbox « » Textfile « » CSV «

1216.67 NA 1216.57896906222 1544.42911895378 1122 1186.17 1216.67 1186.32706637457 1366.3834494132 1191,3 1217.475 1213.62 1217.61518741362 1394.74447514204 1849,75 1096.95 1214.0055 1097.13722496335 1435.70978225614 1159,8 1685.6 1202.29995 1685.35698835458 1515.17300887526 1441,8 1758.5 1250.629955 1758.44429928912 1913.84222078324 1577,3 1786.6 1301.4169595 1786.57095582242 1957.10781265414 1537,8 2049.895 1349.93526355 2049.71036034501 2003.16986500382 1732,3 1845.895 1419.931237195 1845.92826649821 2094.36317239399 1932,3 2015.02 1462.5276134755 2014.98176910371 1946.73777811992 1781,5 1609.63 1517.77685212795 1609.54241047328 1915.17835198758 1504 918.725 1526.96216691516 918.654492873966 1514.01237467182 1155,75 1240.96 1466.13845022364 1240.97493327842 1137.92569933516 1243,5 1671.785 1443.62060520128 1671.67364264948 1425.79213659270 1479,5 2451.83 1466.43704468115 2451.42825634976 1747.14542398917 NA 1886.14 1564.97634021303 1886.27704742758 2134.15076490796 2076 2110.66 1597.0927061 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	2 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk

Model Performance
#	Complexity	split	relative error	CV error	CV S.D.
1	0.659	0	1	1.021	0.167
2	0.188	1	0.341	0.438	0.081
3	0.079	2	0.153	0.176	0.037
4	0.01	3	0.074	0.174	0.038

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/May/26/t1274871352f8rik8ythou3ogg/1lfed1274871291.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274871352f8rik8ythou3ogg/1lfed1274871291.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274871352f8rik8ythou3ogg/2lfed1274871291.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274871352f8rik8ythou3ogg/2lfed1274871291.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274871352f8rik8ythou3ogg/3lfed1274871291.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274871352f8rik8ythou3ogg/3lfed1274871291.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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