Displaying 20 results from an estimated 500 matches similar to: "mvpart error"
2009 Mar 15
0
mvpart error - is.leaf
Hello,
When trying to run mvpart either specifying my own parameters or using the
defaults, I get the following error:
Error in all(is.leaf) :
unused argument(s) (c(FALSE, TRUE, FALSE, FALSE, TRUE, TRUE, TRUE))
As far as I can tell, is.leaf is part of the dendrogam package, so I'm
assuming there's some problem with the graphical parameters. However running
same formula and data
2011 Sep 13
1
mvpart analyses with covariables
Hi all,
I am fairly new to R and I am trying to run mvpart and create a MRT using
explanatory variables and covariables. I've been following the procedures in
Numerical Ecoogy with R.
The command (no covariables) which works fine -
ABUNDTMRT <- mvpart(abundance ~
.,factors,margin=0.08,cp=0,xv="1se",xval=nrow(abundance),xvmult=100,which=4)
where abundance is 4th root
2006 Mar 08
1
function gdist, dist and vegdist in mvpart
Dear R community,
I am analyzing plant communities with the function mvpart, using a
dissimilarit matrix as input. The matrix is calculated with the funtion
gdist.
fit <- mvpart(gdist (ba12[,18:29], meth="maximum", full=TRUE,
sq=F) ~ beers + slope_dem + elev_dem+ plc_dem + pr_curv+
+curv+max_depth+doc_rocks+ abandon+land_use+ca_old,
data=ba12, xv="p")
This
2012 Apr 23
1
change color scheme in mvpart
Hello everyone, I am currently using the mvpart package and would like to change the color scheme it uses, and was hoping someone could help me out. All of the papers I have found have used a grayscale but I can't seem to figure out how they did that! Currently, mvpart plots barplots in a repeating sequence of 3 shades of blue. So if you have 6 response variables the same shade of blue is used
2010 Feb 26
2
Error in mvpart example
Dear all,
I'm getting an error in one of the stock examples in the 'mvpart' package. I tried:
require(mvpart)
data(spider)
fit3 <- rpart(gdist(spider[,1:12],meth="bray",full=TRUE,sq=TRUE)~water+twigs+reft+herbs+moss+sand,spider,method="dist") #directly from ?rpart
summary(fit3)
...which returned the following:
Error in apply(formatg(yval, digits - 3), 1,
2010 Aug 13
3
Delete rpart/mvpart cross-validation output
Dear all,
I was wondering if there is a simple way to avoid printing the multiple
cross-validation automatic output to the console of recursive partitionning
functions like rpart or mvpart. For example...
> data(spider)
>
mvpart(data.matrix(spider[,1:12])~herbs+reft+moss+sand+twigs+water,spider,xv="1se",xvmult=100)
*X-Val rep : 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
2008 Feb 29
1
controlling for number of elements in each node of the tree in mvpart
Still about the mvpart.
Is there any way I can control for the number of elements in each node
in the function mvpart? Specifically, how can I ask partition to
ignore node with elements less than 10?
Thanks!
-Shu
2008 Feb 29
1
barplot and pca plot in mvpart/rpart
Hello,
I'm using the R package called mvpart, which is about the multivariate
regression trees.
The function I wrote is:
mrt1<- mvpart(coefmat~sChip+sScreen+sMem,data=mixdata, xv="pick",
plot.add=TRUE,uniform=TRUE,which=4,all=TRUE,xadj=2,yadj=2,rsq=TRUE,big.pts=TRUE,wgt.ave.pca=TRUE,legend=TRUE,bars=F,
pca=TRUE)
where "coefmat" is a matrix(of dimension N*K) to store
2005 Aug 08
2
INDVAL and mvpart
Hi,
I'd like to perform Dufrene-Legendre Indicator Species Analysis for
a multivariate regression tree. However I have problems with arguments
of duleg(veg,class,numitr=1000)function. How to obtain a vector of
numeric class memberships for samples, or a classification object
returned from mvpart?
thanks in advance
--
Best regards,
Agnieszka Strzelczak
2006 Dec 28
3
CV by rpart/mvpart
Dear R-list,
I am using the rpart/mvpart-package for selecting a right-sized regression tree by 10-fold cross-validation. My question: Is there a possibility to find out for every observation in which of the ten folds it is lying? I want to use the same folds for validating another regression method (moving averages) in order to choose the better one.
Thanks a lot,
Pedro
2010 Apr 26
1
mvpart : Printing response values at terminal nodes
I have created a multivariate regression tree using mvpart, with 3-4
responses. Though the plot shows bargraphs for each response, I would
like to have the VALUES of the responses
printed or indicated (via a scale or something) alongside the bargraph.
Is this possible ??
Thanks,
Manjunath
[[alternative HTML version deleted]]
2010 Mar 12
1
using xval in mvpart to specify cross validation groups
Dear R's
I'm trying to use specific rather than random cross-validation groups
in mvpart.
The man page says:
xval Number of cross-validations or vector defining cross-validation groups.
And I found this reply to the list by Terry Therneau from 2006
The rpart function allows one to give the cross-validation groups explicitly.
So if the number of observations was 10, you could use
2004 Feb 17
0
New package -- mvpart
The package mvpart is now available.
mvpart includes partitioning based on (1) multivariate numeric responses and
(2) dissimilarity matrices.
The package mvpart is a modification of rpart --
-- authors of original: Terry M Therneau and Beth Atkinson
<atkinson at mayo.edu>, and
R port of rpart Brian Ripley <ripley at stats.ox.ac.uk>.
Includes some modified routines from vegan --
2004 Feb 17
0
New package -- mvpart
The package mvpart is now available.
mvpart includes partitioning based on (1) multivariate numeric responses and
(2) dissimilarity matrices.
The package mvpart is a modification of rpart --
-- authors of original: Terry M Therneau and Beth Atkinson
<atkinson at mayo.edu>, and
R port of rpart Brian Ripley <ripley at stats.ox.ac.uk>.
Includes some modified routines from vegan --
2012 Apr 24
0
mvpart versus SPSS
I have a question relating to mvpart, which I hope you can answer.
We recently conducted a study using TBR. In our first study, we used
"regular" TBR in SPSS to model 1 dependent variable. Note we have a
relatively small data-set of 100 cases. In SPSS, we used a minimum change of
improvement smaller than 0.000001 as a stopping rule. Also, we chose the 1SE
"rule", set the
2008 Sep 16
1
1-SE rule in mvpart
Hello,
I'm using mvpart option xv="1se" to compute a regression tree of good size
with the 1-SE rule.
To better understand 1-SE rule, I took a look on its coding in mvpart, which
is :
Let z be a rpart object ,
xerror <- z$cptable[, 4]
xstd <- z$cptable[, 5]
splt <- min(seq(along = xerror)[xerror <= min(xerror) + xvse * xstd])
I interprete this as following: the
2010 Sep 07
1
Multivariate Regression Trees: how to identify sample units?
Dear friends,
I am sudying the mvpart package, that implements Multivariate
Regression Trees, aiming at applying it to a biogeographical dataset of
tree speces in southern South America.
My doubt is how to access plot identities after the tree is produced.
For us it is rather important, but I could not find them with neither
'summary(fit)'[where fit is the object containing the
2008 Oct 01
0
xpred.rpart() in library(mvpart)
R-users
E-mail: r-help@r-project.org
Hi! R-users.
http://finzi.psych.upenn.edu/R/library/mvpart/html/xpred.rpart.html
says:
data(car.test.frame)
fit <- rpart(Mileage ~ Weight, car.test.frame)
xmat <- xpred.rpart(fit)
xerr <- (xmat - car.test.frame$Mileage)^2
apply(xerr, 2, sum) # cross-validated error estimate
# approx same result as rel. error from printcp(fit)
apply(xerr, 2,
2008 Feb 29
0
barplot and pca plot in mvpart
Hello,
I'm using the R package called mvpart, which is about the multivariate
regression trees.
The function I wrote is:
mrt1<- mvpart(coefmat~sChip+sScreen+sMem,data=mixdata, xv="pick",
plot.add=TRUE,uniform=TRUE,which=4,all=TRUE,xadj=2,yadj=2,rsq=TRUE,big.pts=TRUE,wgt.ave.pca=TRUE,legend=TRUE,bars=F,
pca=TRUE)
where "coefmat" is a matrix(of dimension N*K) to store
2004 Nov 09
1
gdist and gower distance
Dear All,
I would like to ask clarifications on the gower distnce matrix calculated by the function gdistin the library mvpart.
Here is a dummy example:
> library(mvpart)
Loading required package: survival
Loading required package: splines
mvpart package loaded: extends rpart to include
multivariate and distance-based partitioning
> x=matrix(1:6, byrow=T, ncol=2)
> x
[,1]