similar to: candisc() error message

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