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B521,regression tree,steven,coomans,thesis,permaand

*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 10:16:23 +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/t12748690354bf3e51om0txxsp.htm/, Retrieved Wed, 26 May 2010 12:17:19 +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/t12748690354bf3e51om0txxsp.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:

B521,regression tree,steven,coomans,thesis,permaand

Dataseries X:

» Textbox « » Textfile « » CSV «

387 NA 342.645625588810 386.613000262070 465 295.5 387 360.224691610665 374.123316633082 299 343.35 377.85 334.57221331123 336.048165995784 516 264.025 374.4 338.051132668702 338.086548077006 320 322.5 363.3625 308.712193932653 307.542001780858 365 392.5 359.27625 314.176745205712 313.784027977660 354 315.75 362.598625 345.218771733043 345.706762345858 408 274.4 357.9137625 333.539349111146 333.558139957923 265 361.875 349.56238625 310.100521795569 309.612466337202 335 411.276 350.793647625 330.620413749521 330.768423422594 388 518.775 356.8418828625 362.586818293621 363.353572983656 397 392.55 373.03519457625 424.489221258347 426.254986865821 444 467 374.986675118625 411.830679983883 412.614239712998 402 382.852 384.188007606763 433.696057002919 434.624717051376 400 449.25 384.054406846086 413.544920914575 413.671773960281 NA 564.252 390.573966161478 427.695992841313 428.070647900106 496 417 407.94176954533 481.817533216771 483.184602478810 475 450.8 408.847592590797 456.128258800945 456.399 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	8 seconds
R Server	'George Udny Yule' @ 72.249.76.132
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	0.71	0	1	1.088	0.167
2	0.055	1	0.29	0.347	0.056
3	0.029	2	0.235	0.366	0.057
4	0.01	3	0.206	0.345	0.057

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/May/26/t12748690354bf3e51om0txxsp/15lg51274868975.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t12748690354bf3e51om0txxsp/15lg51274868975.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t12748690354bf3e51om0txxsp/25lg51274868975.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t12748690354bf3e51om0txxsp/25lg51274868975.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t12748690354bf3e51om0txxsp/3fcx81274868975.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t12748690354bf3e51om0txxsp/3fcx81274868975.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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