Displaying 20 results from an estimated 1100 matches similar to: "candisc() error message"
2008 Dec 10
1
trouble loading candisc
Hello,
I am having trouble loading the package candisc onto my R distribution. I am
using 2.7.1-2. I do a "> install.packages("candisc"
and get the following output.
Warning in install.packages("candisc") :
argument 'lib' is missing: using '/usr/local/lib/R/site-library'
--- Please select a CRAN mirror for use in this session ---
Loading Tcl/Tk
2009 Jan 19
1
candisc
Hello,
I have a question regarding the candisc package. My data are:
species three five
1 2.95 6.63
1 2.53 7.79
1 3.57 5.65
1 3.16 5.47
2 2.58 4.46
2 2.16 6.22
2 3.27 3.52
I put these in a table and then a linear model
>newdata <- lm(cbind(three, five) ~ species, data=rawdata)
and then do a candisc on them
>candata<-candisc(newdata)
2009 Mar 31
1
Package candisc
Hi listers,
I am working on an canonical discriminant analysis, but I am having some
trouble to use the CANDISC function... I just installed the last R version
and installed the package CANDISC... But, I am getting the following message
because about a permission:
The downloaded packages are in
C:\Users\Marcio\AppData\Local\Temp\Rtmpz2kFUm\downloaded_packages
updating HTML package descriptions
2010 Jan 03
1
Anova in 'car': "SSPE apparently deficient rank"
I have design with two repeated-measures factor, and no grouping
factor. I can analyze the dataset successfully in other software,
including my legacy DOS version BMDP, and R's 'aov' function. I would
like to use 'Anova' in 'car' in order to obtain the sphericity tests
and the H-F corrected p-values. I do not believe the data are truly
deficient in rank. I
2008 Dec 11
1
candisc plotting
Hello,
I have a file with two dependent variables (three and five) and one
independent variable. I do i.mod <- lm(cbind(three, five) ~ species,
data=i.txt) and get the following output:
Coefficients:
three five
(Intercept) 9.949 9.586
species -1.166 -1.156
I do a" i.can<-candisc(i.mod,data=i):
and get the following output:
Canonical Discriminant Analysis
2010 May 06
1
How to solve: Error with Anova {car} due to "deficient rank" ?
Hello all,
I am getting the following error:
Error in linear.hypothesis.mlm(mod, hyp.matrix.1, SSPE = SSPE, V = V, :
The error SSP matrix is apparently of deficient rank = 7 < 11
After running:
mod.ok <- lm(as.matrix(dat[,-1]) ~ DC, data=dat)
(av.ok <- Anova(mod.ok, idata=idata, idesign=~week))
Although if I jitter the data in "dat", the function seems to work.
What
2010 Jul 29
0
[R-pkgs] heplots 0.9-3 and candisc 0.5-18 released to CRAN
I've just released the latest R-Forge versions of heplots 0.9-3 and
candisc 0.5-18 to CRAN.
They should appear there within a day or two.
== heplots
The heplots package provides functions for visualizing hypothesis tests
in multivariate linear models (MANOVA, multivariate multiple regression,
MANCOVA, etc.). They
represent sums-of-squares-and-products matrices for linear hypotheses
and for
2008 Jun 07
1
Multivariate LM: calculating F-values after calling linear.hypothesis
Dear R users,
I am analyzing several response variables (all scaled to [0;1]) using a
multivariate linear model.
After fitting the model, I set up a hypothesis matrix to test specific
contrasts for these response variables; for example: "a always increases
significantly more than b when regressed against x".
What I am stuck with now is how to calculate the correct F-values (and
2012 Jan 31
0
Error in linearHypothesis.mlm: The error SSP matrix is apparently of deficient rank
Hi,
I have encountered this error when attempting a One-way Repeated-measure ANOVA
with my data.
I have read the "Anova in car: SSPE apparently deficient rank" thread
by I'm not sure the within-subject interaction has more degrees of freedom
than subjects in my case.
I have prepared the following testing script:
rm(list = ls())
2008 Apr 18
0
new candisc package on CRAN
I'm happy to announce the candisc package, v 0.5-9, now on CRAN.
Generalized Canonical Discriminant Analysis
Description
This package includes functions for computing and visualizing
generalized canonical discriminant analyses for a multivariate linear
model. They are designed to provide low-rank visualizations of terms in
a mlm via the plot method and the heplots package.
The methods
2008 Apr 18
0
new candisc package on CRAN
I'm happy to announce the candisc package, v 0.5-9, now on CRAN.
Generalized Canonical Discriminant Analysis
Description
This package includes functions for computing and visualizing
generalized canonical discriminant analyses for a multivariate linear
model. They are designed to provide low-rank visualizations of terms in
a mlm via the plot method and the heplots package.
The methods
2008 Apr 03
2
coding for categorical variables with unequal observations
Hi,
I am doing multiple regression, and have several X variables that are
categorical.
I read that I can use dummy or contrast codes for that, but are there
any special rules when there're unequal #observations in each groups (4
females vs 7 males in a "gender" variable)?
Also, can R generate these codes for me?
THanks.
2012 Feb 08
2
dropterm in MANOVA for MLM objects
Dear R fans,
I have got a difficult sounding problem.
For fitting a linear model using continuous response and then for re-fitting the model after excluding every single variable, the following functions can be used.
library(MASS)
model = lm(perf ~ syct + mmin + mmax + cach + chmin + chmax, data = cpus)
dropterm(model, test = "F")
But I am not sure whether any similar functions is
2013 Jan 29
3
how to suppress the intercept in an lm()-like formula method?
I'm trying to write a formula method for canonical correlation analysis,
that could be called similarly to lm() for
a multivariate response:
cancor(cbind(y1,y2,y3) ~ x1+x2+x3+x4, data=, ...)
or perhaps more naturally,
cancor(cbind(y1,y2,y3) ~ cbind(x1,x2,x3,x4), data=, ...)
I've adapted the code from lm() to my case, but in this situation, it
doesn't make sense to
include an
2008 Jul 01
2
PCA : Error in eigen(cv,
Hi all,
I am doing bootstrap on a distance matrix, in which samples have been
drawn with replacement. After that I do PCA on a resulted matrix, and
these 2 steps are repeated 1000 times.
pca(x) is a vector where I wanted to store all 1000 PCAs; and x is from
1 to 1000
SampleD is a new matrix after resampling;
I am getting the following error message, which I don't understand:
....
2008 Oct 29
2
sessionInfo() error
[Using R 2.7.2 on Windows XP]
After re-building our heplots package, I've begun to get the following
error from sessionInfo(),
even though it passes R CMD check and builds without errors:
> sessionInfo()
Error in x$Priority : $ operator is invalid for atomic vectors
In addition: Warning message:
In FUN(c("MASS", "heplots", "car", "rgl",
2004 Apr 15
1
residuals
I'm trying to determine the lack of fit for regression on the following:
data <- data.frame(ref=c(0,50,100,0,50,100),
actual=c(.01,50.9,100.2,.02,49.9,100.1),
level=gl(3,1))
fit <- lm(actual~ref,data)
fit.aov <- aov(actual~ref+Error(level),data)
According to the information I have, the lack of fit for this regression is
the
2007 Sep 12
0
constructing an lm() formula in a function
I'm working on some functions for generalized canonical discriminant
analysis in conjunction with the heplots package. I've written a
candisc.mlm function that takes an mlm object and computes a
candisc object containing canonical scores, coeficients, etc.
But I'm stumped on how to construct a mlm for the canonical scores,
in a function using the *same* right-hand-side of the model
2018 May 26
0
TukeyHSD for multiple response
Hi Sergio
Doing those tests 30 times is going to give you a huge Type I error
rate, even if there was a function that did that. There is a reason
why TukeyHSD doesn't make it easy.
In general, if there are useful comparisons among the species, you are
better off setting up and testing contrasts than doing all-pairwise
Tukey tests.
Also, the PCA scores are ordered in terms of variance
2005 Jul 06
1
Help: Mahalanobis distances between 'Species' from iris
Dear R list,
I'm trying to calculate Mahalanobis distances for 'Species' of 'iris' data
as obtained below:
Squared Distance to Species From Species:
Setosa Versicolor Virginica
Setosa 0 89.86419 179.38471
Versicolor 89.86419 0 17.20107
Virginica 179.38471 17.20107 0
This distances above were obtained with proc