similar to: computationally singular and lack of variance parameters in SEM

Hello, I am trying to create multiple matrices (to run a PVA) but can't import all of them from a .csv without the numbers treated as labels and not factors. I can enter the matrix slowly: Site05_96 <- matrix(c(0.07,0,0.03,0.00,NA,0.00, 0.09,0.166666667,0.31,0.42,NA,0.00, 0.00,0,0.00,0.00,NA,0.00, 0.00,0,0.00,0.00,NA,0.00,

Dear All, I am analysing a dataset on levels of herbivory in seedlings in an experimental setup in a rainforest. I have seven classes/categories of seedling damage/herbivory that I want to analyse, modelling each separately. There are twenty maternal trees, with eight groups of seedlings around each. Each tree has a TreeID, which I use as the random effect (blocking factor). There are two

Dear members of the R help list, I want to do a hierarchical glm with binomial family but am unsure about how to write the syntax which involves nesting. I want to test whether the risk of being attacked by Herbivores for Meadowsweet plants is significantly dependent on the Distance to heterospecific source plants. Dependent variable = Herbivory (yes/no) Explanatory continuous variable =

Dear all, I'm quite sure that this is a stupid question, but I'll ask anyway. I want to perform an ANCOVA with two continuous factors and three categorical factors. Plant population growth rate (GR) = dependent variable Seed reduction due to herbivory (SR) = continuous explanatory variable Herbivore species (HS, 2 levels) = categorical explanatory variable Population (Pop, 24 levels) =

Hello list, I'm trying to make sure that I'm performing a path analysis correctly using the sem package. the figure at http://flame.cs.dal.ca/~sstewart/regressDiag.png has a detailing of the model. The challenge I'm having is that reuse is an indicator (0/1) variable. Here's the code I'm using: corr =

Dear All, I am new for R and SEM. I try to fit the model with Y (ordinal outcome), X (4 categorical data), M1-M3 (continuous), and 2 covariates (Age&sex) as a diagram. library(polycor) model.ly <-specify.model() 1: x -> m1, gam11, NA 2: x -> m2, gam12, NA 3: x -> m3, gam13, NA 4: age -> m1, gam14, NA 5: age -> m2, gam15, NA 6: age -> m3, gam16, NA 7: sex -> m1,

Dear all, I am trying to define my own corStruct which is different from the classical one available in nlme. The structure of this correlation is given below. I am wondering to know how to continue with this structure by using specific functions (corMatrix, getCovariate, Initialize,...) in order to get a structure like corAR1, corSymm which will be working for my data. Thanks in advance.

Full_Name: Benjamin Tyner Version: 2.6.0 RC 2007-10-01 r43043 OS: WinXP Submission from: (NULL) (171.161.224.10) platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status RC major

R-helpers, n <- 100 arcoefs <- c(0.8) macoefs <- c(-0.6) p <- length(arcoefs) q <- length(macoefs) require(nlme) tmp <- corARMA(value=c(arcoefs,macoefs), form=~1, p=p, q=q) Sigma <- corMatrix(tmp, covariate = 1:n) # results in segfault Have I used these commands in an improper way? Thanks Ben

Hi all, When running a prediction using RF on another data, I get two columns returned: row number(?) and predicted class. Is there a way of appending the unique row value from an ID column in the dataframe to the predictions instead of the row number? I'm assuming that the returned results follow the data frame in that the first result returned equals the first entry in the dataframe. i.e.,

Hi have been trying to get winbind working on Solaris 9 but to no effect. version info: samba: 3.0.0 openldap: 2.1.23 kerberos: MIT 1.3.1 Have followed the instructions in every howto, usenet posting I could find: nscd not running created relevant links in /lib and /lib/security/sparcv9 applied patch for nsswitch as recommended kinit -e works net ads join works wbinfo -t works wbinfo -u

Dear Friends, I am seeking for any help on an error message in lme functions. I use mixed model to analyze a data with compound symmetric correlation structure. But I get an error message: "Error in corMatrix.corCompSymm(object) : NA/NaN/Inf in foreign function call (arg 1)". If I change the correlation structure to corAR1, then no error. I have no clue how to solve this problem.

  Hola,   Por favor, ¿podríais indicarme qué recursos (librerías o ideas) pueden resultar de utilidad para crear un gráfico del estilo del de la figura 3.8 del siguiente link?   http://www.tsc.uvigo.es/BIO/Bioing/ChrLDoc3.html#3.5   Actualmente estoy utilizando funciones muy básicas y la verdad es que no me encuentro muy satisfecha con el resultado.   Muchas gracias.   Eva [[alternative HTML

Hi, I have been using the function lme() of the package nlme to model grouped data that is auto-correlated in time and in space (the data was collected on different days via a moving monitor). I am aware that I can use the correlation classes corCAR1 and corExp (among other options) to model the temporal and spatial components of the auto-correlation. However, as far as I can tell, I can only

Dear all, I'm discovering the somehow confusing (for me) world of linear mixed models after having been advised it could be the best option to analyze my dataset. After several days of reading, I'm not sure that what I ended up with makes some sense and I'd greatly appreciate any help and explanations. The dataset has been obtained as follows. In 15 different locations, I counted

Hi there, Here is my situation: > User NEWBIE!!!!! > version _ platform i386-pc-mingw32 arch x86 os Win32 system x86, Win32 status major 1 minor 2.2 year 2001 month 02 day 26 language R I wonder why. Given this data

Let's say I would like to look inside the function corBrownian in library (ape). When I type in the function name I get the following, which is not nearly the detail that goes into this function. I am wondering how to begin cracking this function open (and others) so I can learn more about it and perhaps code my own corClass one day. Thanks. > corBrownian function (value = 1, phy, form

Hi list. I was saving my modified pairs graphic using a custom panel from the R Graphics site, and I got an interesting difference in the final image when I save it as eps or png. This custom panel make possible to show at the left side of the pairs plot the p-value as symbol and the correlation r value with its cex proportional to the r value itself. Well, when saving as a png file

I am after a nice way to disable (not destroy, delete nor nullify) all associated records. I''m a hoarder, I don''t want to get rid of anything but I want to stop records being visible. I have a disabled boolean in my tables and if I disable the top record in the association (say the association is 5-6 levels deep), I would like to cleanly disable its children. I''ve

Let me modify my question about user-defined covariance structures for LME models: Can somebody tell me how I can see the code for the definition of the correlation structures that come with the NLME package. Specifically I like to see the code for the functions coef, corMatrix, and intialize for any of the pre-defined correlation structures, and use this as a template to define a new correlation