search for: corrmatrix

Dear All,   wondering if someine can access the link to the randsamp code referenced in the R-help archive here: http://www.mail-archive.com/r-help@stat.math.ethz.ch/msg75645.html ? I have tried but for whatever reason I can not get trough. My problem seems to be similar to what the author originally described there, so having access to it would be great. Else, if you have any thougths on sampling

...opposed to the alternating top-bottom scale approach. Also, I would like to increase the font size of the graphic for print purposes. Any help on how to accomplish this would be greatly appreciated! Thanks, Mark Here is the code I am using for this analysis: data <- read.table("X:/GWRclip/corrmatrix.txt", header = T) ASHDEP <- data [,1] ELE <- data [,2] SLP <- data [,3] ASP <- data [,4] PLCU <- data [,5] PRCU <- data [,6] CTI <- data [,7] STI <- data [,8] SPI <- data [,9] data <- data.frame(ASHDEP, ELE, SLP, ASP, PLCU, PRCU, CTI, STI, SPI) hetcor(data) # Pea...

Hi, Does anyone know how to extract fixed effects SE values from generalized linear mixed models estimated using the lmer function in the lme4 library? I searched attributes and structure with no luck. Thanks Frank A. La Sorte, Ph.D. Department of Fisheries and Wildlife Sciences University of Missouri Columbia, MO 65211 USA

...A <- array ( rep ( 1 : 36 , by = 4 ), dim = c ( 12 , 3 , 4 )) #Load 'geomorph' package and superimpose coordinates test.gpa <- gpagen ( A , print.progress = FALSE ) #Load 'paleomorph' and generate covariance and correlation matrices cvmatrix <- dotcvm ( test.gpa $ coords ) corrmatrix <- dotcorr ( test.gpa $ coords ) Then I do a clustering with Ward method and euclidean distance, using the cvmatrix and I get a dendrogram. This part is not the problem, so I'll go directly to what I want. I would like to calculate the mean correlation between the elements of each cluster...

For a Monte Carlo study I need to extract from an lme model the estimated standard deviation of a random effect and store it in a vector. If I do a print() or summary() on the model, the number I need is displayed in the Console [it's the 0.1590195 in the output below] >print(fit) >Linear mixed-effects model fit by maximum likelihood > Data: datag2 > Log-likelihood: