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Windows 2000 . 5.00.2195 with Service Pack 1. R 1.5.1 Output from my split-split plot aov "alerted" me that I have done something wrong. I designed an experiment with all combinations of all levels of each treatment, but lost a little data (3 out of 192 plots). With the following data, I run the following model: > collim[c(1:6,187:192),c(1,3:6,9)] plot Litter Fert

Hi, I've data from an incomplete fatorial design. One level of a factor doesn't has the levels of the other. When I use lm(), the summary() return NA for that non estimable parameters. Ok, I understant it. But I use contrast::contrast(), gmodels::estimable(), multcomp::glht() and all these fail when model has NA estimates. This is becouse vcov() and coef() has different dimensions. Is

Windows 2000 (v.5.00.2195), R 1.5.1 I have an lme object, fm0, which I examine with anova() and intervals(). The anova output indicates one of the interaction terms is significant, but the intervals output shows that the single parameter for that term includes 0.0 in its 95% CI. I believe that the anova is a conditional (sequential) test; is intervals marginal or approximate? Which should I

Hi R users, I sent a message yesterday about NA in model estimates ( http://r.789695.n4.nabble.com/How-set-lm-to-don-t-return-NA-in-summary-td3722587.html). If I use aov() instead of lm() I get no NA in model estimates and I use gmodels::estimable() without problems. Ok! Now I'm performing a lot of contrasts and I need correcting for multiplicity. So, I can use multcomp::glht() for this.

foreign package does not support dataset saved at stata 13. anyone knows any wayt to make it works? [[alternative HTML version deleted]]

Dear R community, I am trying to fit an nlme model where I want to estimate the fixed effects of two treatments on the parameters on the following equation Photo~(a*(1-exp(-c*PARi/a)))-b I was able to fit a simple model without covariates following the method described in Mixed-Effects Methods and Classes for S and S-PLUS, version 3.0, but when I add the covariates, I get the error "

Hi R-Helpers: I?m trying to use the function GLMM from lme4 package, (R-1.8.1, Windows 98),and I get the following error: > pd5 = GLMM(nplant~sitio+ + fert+ + remo+ + sitio:fert+ + remo:sitio+ + remo:fert+ + remo:fert:sitio + data=datos, + family=binomial, +

Using R v. 1.7.0 on Windows 2000 I would like to plot the fitted values of a model as a function of a continuous covariate, augmented with data (e.g., augPred) grouping by combinations of fixed effects. I have not been able to use augPred effectively, and am wondering if it does not handle unbalanced data (3 out of 192 missing). I include below the model and an xyplot that almost does the

Hello, I am a Masters student and I am working on my thesis modelling smallholder farms using a program in R. I have modified the original code and I am having some issues with lists that I cannot figure out. Originally, I had list file defining lists such as: Param, Crop1, Crop1, Soil, etc. (ex. Param <- list() ). Their subsets were listed as Crop1$CContent for example and there was quite

Hi I have a file saved in R, named agrexp.Rdata, shown below > agrdata fert yield 1 25 84 2 50 80 3 75 90 4 100 154 5 125 148 If I double clicked on this file, the data is displayed without problem. However if I tried to import using: > agrdata<-read.table("agrexp.Rdata") or >

Dear all I'm not sure if I did the right analysis for my specific split splot design. We are studying biomass increase with different CO2 concentrations with four different functional plant groups (e.g. grasses, herbs, broad-leafed trees and conifers). Of each functional plant group we have four species. The design is orthogonal. The design is: Blocks: 2 (climate chambers, called

Hi Rneters, I'm running a GLM model with a full factorial design in blocks and binomial error distribution. I would like to have the F values for this model but I got a message that "using F test with a binomial family is inappropriate in: anova.glm(model, test = "F")". Should I not report F statistics on this kind of analysis? I would appreciate any comment on this.

Hi, I'm trying to fit a logit model to a set of data that was collected under a split plot scheme. The structure of the data is Whole plot factors: Watering Frequency (2 levels: Hi/Lo) and Fertilizer type (3 factors A/B/C) Subplot factor: slope type (2 factors up/down) Response: Proportion of infected leaves(Infected leaves/Total leaves) of the plant (2 plants recorded from each plot)

Hello, I'm fairly new to linux so i home i am making sense ;) I've tried to run TOCA Race driver 3 with wine, however at first I had problem with d3dx9_36.dll so I treid to put it in the folder of TOCA and it worked somehow but then i ran into another problem - now only a black screen flashesh giving this - http://pastebin.com/m685264c4 I hope you can help me understand why. P.S. As I

Simple Question I have 100x100 matrix and I want to calculte each row's 30,50% quantile ex) a=matrix(rnorm(10000),100,100) quantile(a[1,],c(0.3,0.5)) quantile(a[2,],c(0.3,0.5)) . . . . I want get results at once. so I try quantile(a[1:100,],c(0.3,0.5)) but I can get what I exactly want. How can I calculte that? -- View this message in context:

Hola a tod@s, Me han mandado una base de datos y al abrirla me he encontrado con la fecha y la hora en el siguiente formato: FECHA HORA 20121007 1206 20110622 1854 20110623 054 He conseguido que la Fecha me quedara en el formato dd/mm/aaaa mediante el script db[, "FECHA"] <- as.Date(as.character(db[,

After some futile searches, I decided to ask the list to see if any of the sages out there would have an answer: I have a function I wrote a few years ago in S, which calls glim numerous times. I'd like to port it to R, but glm works differently from glim, which takes as part of its input an X design matrix. I probably could write a function to convert glim to glm, but hope this

Full_Name: Claus Pastor Version: 2.9.2 OS: Windows XP Submission from: (NULL) (82.113.106.4) I use the following function to compute MutualInformation Matrix of factorial members of a dataframe. I use package minet for this: my.MI = function(test) { ## die Diagonale gibt die Entropien, Teile durch entropy von y und du erh?lst den Zusammenhang ## kenne X und sage daraus y voraus require(minet)

Hi All, I have been reading about general purpose GPU (graphical processing units) computing for computational statistics. I know very little about this, but I read that GPUs currently cannot handle double-precision floating points and also that they are not necessarily IEEE compliant. However, I am not sure what the practical impact of this limitation is likely to be on computational

Hola a todos Estoy cargando una base de datos a R llamada "Base", desde excel. A la hora de utilizar funciones como: >pairs(Base) Error in pairs.default(Base) : non-numeric argument to 'pairs' Una forma de arreglar este problema es utilizando la funcion as.numeric(), pero me toca hacerlo variable por variable: >Base$Variable1<-as.numeric( Base$Variable1)