similar to: forming a linear discriminant function from the output of lda()

This bottle of Quoi D?Neuf by Herv? Villemade, a primeur from the Loire, was a real pleasure, a thirst wine that you sip without second thoughts and restriction to the last drop : This Pinot Noir with a bit of Gamay is fruity, gouleyant and fresh. This proves that even tasted several months after its release, a Vin Nouveau can deliver. It arrived on the market on the third thursday of november

This is an update on the current status of the relicensing, but also an opportunity to give feedback. Sorry it's rather long, but I think it's necessary to summarise the situation - there are probably list members who weren't even born at the start of the history of this! Xapian is currently licensed as GPLv2+, but isn't something we actually chose for Xapian, but rather due to a

Hello All: I have a binomial model with one covariate, x1, treated as a factor with 3 levels. The other covariate is measured x2 <- 1:30. The response, y, is the proportion of successes out of 20 trials. glm(cbind(y, 20 - y) ~ x1 * x2, family = binomial) Now, I would like to constrain the cofficients on 2 levels of the factor, x1, to be identical and test the difference between these

Hi all, Daniele Favara was kind enough to package Xapian (and Pinot :-) for Dapper and Xubuntu. I understand Daniele used cdbs to build these packages. http://packages.debian.org/unstable/devel/cdbs I am not sure if the differences with the official packages built for Debian and Breezy are significant... Anyway, if you would like to give them a go, add the following to your sources.list : deb

Hello, Apologies if this question has already arised, hope you can help me to the find the solution to this or point the place to look at. I have a multidimensional piece-wise regression linear problem, i.e. to find not only the regression coefficients for each "interval" but also the beginning and ends of the intervals. To simplify it to the one dimensional case and two intervals,

Dear R-group, I am trying desperately to get this Tukey test working. Its my first time here so I hope my question is not too stupid, but I couldn't find anything helpful in the help or in the forum. I am analysing a dataset of treated grasses. I want to find out, if the grasses from different Provenances react differently. In the aov test I found a significance for the combination Treatment

Dear R-devel'ers Below is an outline for a set of routines to improve support for multivariate linear models and "classical" repeated measurements analysis. Nothing has been coded yet, so everything is subject to change as loose ideas get confronted by the harsh realities of programming. Comments are welcome. They might even influence the implementation... -pd General

Hi r-users,   I would like to extract the data that match.  Attached is my data: I'm interested in matchind the value in column 'intg' with value in column 'rand_no' > cbind(z=z,intg=dd,rand_no = rr)             z  intg rand_no    [1,]  0.00 0.000   0.001    [2,]  0.01 0.000   0.002    [3,]  0.02 0.000   0.002    [4,]  0.03 0.000   0.003    [5,]  0.04 0.000   0.003    [6,] 

I am working on my thesis in which i have couple of independent variables that are categorical in nature and the depndent variable is dichotomus. Initially I run univariate analysis and added the variables with significant p-values (p<0.25) in my full model. I have three confusions. Firstly, I am looking for confounding variables by using formula "(crude beta-cofficient - adjusted

On 09/10/2017 04:14 PM, Jack Bailey wrote: > Hello, > > I'm taking 7.4 for a spin.? I did the minimal install, and ran into > trouble with groupinstall base.? The trouble seems to stem from > elfutils.? One command claims elfutils-libs-0.166-2.el7.x86_64 is > missing, and another one claims it's installed.? Not sure what's going > on here. > > [root at

Hello, I'm taking 7.4 for a spin.? I did the minimal install, and ran into trouble with groupinstall base.? The trouble seems to stem from elfutils.? One command claims elfutils-libs-0.166-2.el7.x86_64 is missing, and another one claims it's installed.? Not sure what's going on here. [root at ip-172-31-34-187 ~]# yum -y install elfutils.x86_64 Loaded plugins: fastestmirror

Good day, All, Is there any way to maintain the number of decimal places in the type of situation below? I would like to maintain the number of decimal places in 0.667, despite the fact that its column-mates have a fourth decimal place. Thank you for your time. Jim dat.txt contents: MARKER ALLELES FREQ1 RSQR EFFECT2 STDERR CHISQ PVALUE rs6599753 C,T

Dear all, I am attempting to explain patterns of arthropod family richness (count data) using a regression model. It seems to be able to do a pretty good job as an explanatory model (i.e. demonstrating relationships between dependent and independent variables), but it has systematic problems as a predictive model: It is biased high at low observed values of family richness and biased low at

Hi R community, I am new bird to R and moved recently from SAS. I am no means expert on either but very curious learner. So your help crucial for me to learn R. I have already got positive expression. I was trying to fit a mixed model in animal experiment but stuck at simple point. The following similar example is from SAS mixed model pp 212. # data genetic_evaluation <-

People, help me please! How to use lm() function to defind a cofficient for 7-polinom, and what expression should I put in /formula/ -- View this message in context: http://r.789695.n4.nabble.com/lm-tp4545740p4545740.html Sent from the R help mailing list archive at Nabble.com.

Full_Name: Adrian Custer Version: 0.90.0 OS: Linux on Thinkpad (pentium) and desktop (K6) Submission from: (NULL) (128.32.251.234) When I create a boxplot, and then try to overlay a lowess fit or just the points, the points do not appear in the highest level and the lowess curve does not reach the highest level. However, if I add one to each of the models, the problem is solved. I tried this

Hi, a while ago I posted a question regarding the use of alternative models, including a quasibinomial mixed-effects model (see Results 1). I rerun the exact same model yesterday using R 2.7.2 and lme4_0.999375-26 (see Results 2) and today using R 2.7.2 and lme4_0.999375-27 (see Results 3). While the coefficient estimates are basically the same in all three regressions, the estimated standard

Hello all, I have just started using fitting the PCM (Partial Credit Model) using eRm and have 2 problems which I cannot solve, I have checked everywhere on the net, but no joy: Firstly, I have fit a PCM model to 10 variables with differing response categories (3 for the first 6 items, 4 for the following 2 and 2 for the last two items). mat1 <- matrix(c(rasch_bart$bart_bowel,

Sadly you failed to set your email program to send plain text and the data is corrupted at my end. I also think you need to reduce the size of the data set... the intent here is to increase your understanding, not debug your particular analysis. I will say that I am having a very challenging time understanding what you are trying to accomplish though. What are the equations that you think need

Hello Chris, I am trying to fit a 4 state multi-state model using hidden markov routine in the msm package. 1. initial parameters: twoway4.q <- rbind(c(0, 0.25, 0, 0.25), c(0.166, 0, 0.166, 0.166), c(0, 0.25, 0, 0.25), c(0, 0, 0, 0)) ematrix <- rbind( c(0, 0.01, 0, 0), c(0.01, 0, 0.01,0), c(0, 0.1, 0, 0), c(0, 0, 0, 0)) 2. the model: msm_covariates_sexandage <- msm(state ~