similar to: Dominant factors in aov?

Hello group, For my PhD I'm working on a spatial sampling grid. I do have two data sets which I'd like to compare using cross-correlograms or cross-variograms. Is this an option in one of the R-packages? I've been searching the R-help archive and the available package-documentations, but I can't find how to do this. Thanks in advance, Ren?.

Hi group, I'm trying to do a Tukey test to compare the means of a factor ("treatment") with three levels in an lme model that also contains the factors "site" and "time": model = response ~ treatment * (site + time) When I enter this model in csimtest, it takes all but the main factor "treatment" as covariables, not as factors (see below). Is it

All, I'm trying to analyze the results of a reciprocal transplant experiment using lme(). While I get the error-term right in aov(), in lme() it appears impossible to get as expected. I would be greatful for any help. My experiment aimed to identify whether two fixed factors (habitat type and soil type) affect the development of plants. I took soil from six random sites each of two types

Hi group, I'd like to do spatial analysis of my data using the spdep package. It appears that a file of class nb is necessary, but I do not find what that should look like and if there is a function that creates such file for me. How can I create a nb-object of my data points? Thanks, René Eschen. [[alternative HTML version deleted]]

Why are the results not reliable? ________________________________ From: ESCHEN Rene [mailto:rene.eschen@unifr.ch] Sent: Wednesday, August 23, 2006 3:48 AM To: Spencer Graves; r-help@stat.math.ethz.ch Cc: Doran, Harold Subject: RE: [R] Random structure of nested design in lme The output of the suggested lmer model looks very similar to the output of aov, also when I ran the model

Group, I'm currently trying to find out how the function correlog in the ncf package may be useful to me for calculating cross-correlograms. The function's output includes P-values for all distance classes, but it seems that only positive values can become significant. Is this true and correct? If so, why? Thanks in advance. Ren? Eschen. _______________________________________ Ren?

I get this message, when opening the winecfg, rn@MX:~$ winecfg fixme:wave:ALSA_AddCaptureDevice Add support for DSCapture fixme:wave:ALSA_AddCaptureDevice Add support for DSCapture fixme:mixer:ALSA_MixerInit No master control found, disabling mixer /bin/sh: /usr/bin/esd: not found fixme:jack:JACK_drvLoad error loading the jack library libjack.so, please install this library to use jack --------

Hi I am working with this data: my data summary is: > summary(spi) open high low close volume Min. :4315 Min. :4365 Min. :4301 Min. :4352 Min. : 0 1st Qu.:4480 1st Qu.:4497 1st Qu.:4458 1st Qu.:4475 1st Qu.:11135 Median :4609 Median :4631 Median :4594 Median :4614 Median :14439 Mean :4620

Hello list, I am currently testing a setup for a PoC wit this configuration. - 1 x Frontend dovecot for proxying IMAP/POP3/LMTP/ManageSieve/Submission - 2 x Backend dovecot with local mail storage The frontend does the user authentification and communicate with the backends using a master password The fronted accepts PLAIN and LOGIN auth mechanisms and talk with backends using PLAIN auth

Hi all. This is perhaps more a statistics question but I'm hoping someone can help me. I have a group of patients for whom I'm looking at beat to beat RR interval changes. I have plotted the difference between one beat length and the next against the difference between the previous beat length and the current one. This gives me a plot with four quadrants: the bottom left corresponding to

Dear all, I have few training on Hidden Markov Model. But, I intend to solve my problem by HMM. I would like to have your helps/directions to me. Here, I have two variables to define the 8 one-dimension space (coordinate.1, coordinate.2). In this one-dimension space, there are two sequences of values (shared and specific). This means I would like to detect/guess/predict the regions (defined by

Dear All, I want to know if there is some easy and reliable way to estimate the number of dominant eigenvalues when applying PCA on sample covariance matrix. Assume x-axis is the number of eigenvalues (1, 2, ....,n), and y-axis is the corresponding eigenvalues (a1,a2,..., an) arranged in desceding order. So this x-y plot will be a decreasing curve. Someone mentioned using the elbow (knee)

Dear R users & Experts, This is just a curiousity, I was wondering why the dominant eigenvetor and eigenvalue of the following matrix is given as the third. I guess this could complicate automatic selection procedures. 0 0 0 0 0 5 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 Please

In the summary of the output of arma, there's a number Pr(>|t|), however, I don't know what is its meaning - at least, it doesn't _seem_ to be a Student's t distribution. Reproducible test case: x <- c(0.5, sin(1:9)) reg <- arma(x, c(1,0)) summary(reg) <output> Call: arma(x = x, order = c(1, 0)) Model: ARMA(1,0) Residuals: Min 1Q Median 3Q

On 31.5.2013 13:04, Miroslav Lichvar wrote: > On Wed, May 29, 2013 at 04:08:57PM +0200, Martijn van Beurden wrote: >> I was surprised to see that the Windows compile on wine actually >> outperformed the native Linux one. Probably GCC 4.6 optimized a little >> better or something very weird is going on in wine, I don't know. The >> assembly optimizations work very

On 28-05-13 20:09, Janne Hyv?rinen wrote: > On Windows the 32-bit NASM enabled compiles are always fastest. If you > can run 32-bit code on your Linux box you should compile with assembly > optimizations. That depends on the way you define speed. For decoding this doesn't seem to be true. I reran my tests, it took a little longer because I couldn't believe the results I got.

Hi, Given a positive integer N, and a real number \lambda such that 0 < \lambda < 1, I would like to generate an N by N stochastic matrix (a matrix with all the rows summing to 1), such that it has the second largest eigenvalue equal to \lambda (Note: the dominant eigenvalue of a stochastic matrix is 1). I don't care what the other eigenvalues are. The second eigenvalue is

Hi I have a question regarding an output of a binomial lmer-model. The model is as follows: lmer(y~diet * day * female + (day|female),family=binomial) The corresponding output is: Generalized linear mixed model fit by the Laplace approximation Formula: y ~ diet * day * female + (day | female) AIC BIC logLik deviance 1084 1136 -531.1 1062 Random effects: Groups Name Variance

Dear all, I'm quite new in R and I have a problem with the function which. When I use it to select a subset of a dataframe it works well but somewhere R takes trace of the past dataframe and this creates problems with following operations. For example: sentences <- read.xls("frasi.tot.march.3.xls", header=TRUE) head(sentences) fam subjID Cond Code reg total first

On Wed, May 29, 2013 at 04:08:57PM +0200, Martijn van Beurden wrote: > I was surprised to see that the Windows compile on wine actually > outperformed the native Linux one. Probably GCC 4.6 optimized a little > better or something very weird is going on in wine, I don't know. The > assembly optimizations work very well on encoding, but actually slow > things down when