similar to: ARMA random effects?

Greetings R-helpers, I am attempting to fit an lme() while specifying a correlation structure, but I'm getting into trouble long before I get to that point. I am receiving the error: Error in y[revOrder] - Fitted : non-conformable arrays It doesn't seem to matter how simple or complex the model I specify is, it always gives this same error message. This makes me suspect something is

Dear All -- I am trying to use within a little table producing code an anova comparison of two gls fitted objects, contained in a list of such object, obtained using nlme function gls. The anova procedure fails to locate the second of the objects. The following code, borrowed from the help page of anova.gls, exemplifies: --------------- start example code --------------- library(nlme) ##

Hi, Well after trying to fix the assign commands in version 3.1.7 of your nlme package I still cannot get the plot functions to work. Basically I have no other packages installed (apart from those provided with R) so nlme is the first. my R version info is; platform sparc-sun-solaris2.7 arch sparc os solaris2.7 system sparc, solaris2.7 status

Hi there, I try to compare the mixed model package "lme" by Splus and R. I used the dataset "Ovary" and the following code assuming AR(1) model for the error term: lme(follicles ~ sin(2*pi*Time) + cos(2*pi*Time), data=Ovary, random = pdDiag(~sin(2*pi*Time) ) , correlation=corAR1() ) But I got different results! And then I used a simpler model: lme(follicles ~

Dear R developers, first of all let me join the chorus of congratulations for the release of R 1.0.0. Well, done! Unfortunately, I find it necessary to e-mail in a bug report regarding the `nlme' package. On my office machine I experience the following trouble: bossiaea:/opt/R$ R CMD check -c nlme Checking package `nlme' ... Massaging examples into `nlme-Ex.R' ... Running

Hi out there, I am trying to fit a species accumulation curve (increase in number of species known vs. sampling effort) for multiple regions and several bootstrap samples. The bootstrap samples represent different arrangements of the actual sample sequence. I fitted a series of nlme-models and everything seems OK, but since the observations are correlated I tried to include some correlation

Dear All: I updated my R program as well as associated packages yesterday. Currently my R version is 2.2.1 running under WINXP SP-2. When I tried to list (summary) an nlme object that I developed before, I got the following error message: [ Error in .C("ARMA_constCoef", as.integer(attr(object, "p")), as.integer(attr(object, : C entry point "ARMA_constCoef"

  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

There has been some recent discussion on this list about the value of using intervals with lme() to check for whether a model is ill-defined. My question is, what else can drive very large confidence intervals for the variance components (or cause the error message "Error in intervals.lme(Object) : Cannot get confidence intervals on var-cov components: Non-positive definite approximate

Hi there fellow R-users, I am trying to follow an example of modelling a serial correlation structure in the textbook "Mixed Effects Model in S and Splus". However, I am getting some very odd results. Here is what I am trying to run: library(nlme) data(Ovary) fm1<-lme(follicles~sin(2*pi*Time)+cos(2*pi*Time),data=Ovary,random=pdDiag(~s in(2*pi*Time))) ### The example is fine up

Trying following example from Pinheiro and Bates in order to fit an ARMA(1,1) model: library(nlme) fm1Ovary.lme<-lme(follicles~sin(2*pi*Time)+cos(*pi*Time),data=Ovary,random=p dDiag(~sin(2*pi*Time))) fm5Ovary.lme<-update(fm1Ovary.lme,corr=corARMA(p=1,q=1)) I get follwing error message: Error in "coef<-.corARMA"(`*tmp*`, value = c(62.3428455941166, 62.3428517930051 :

Hola:   Tengo un modelo de regresión lineal en el cual las componentes son cosenoidales, y lo construyo del siguiente modo:     modelo = "y ~ I(t) + I(t^2) + I(t^3) + x1[, 1] + x2[, 1]" x1[, 1] = cos(2 * pi * t / periods[1]) x2[, 1] = sin(2 * pi * t / periods[1]) for (i in 2:nComp) {   x1[, i] = cos(2 * pi * t / periods[i])   x2[, i] = sin(2 * pi * t / periods[i])   modelo =

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about something else than the IP Trunk, he is talking about outbound (which is related to using an application to run an outside call, which is used usually in campaign in contact centers and so on), I think nthis case differs that placing a calls via IP Trunk or even outside call but the caller who will do it (and not the application). Lastly, Mr. Amit helped me when he gave me a configuration

Hi, I'm new to this mailing list so apologies if this is too basic. I have confocal images 512x512 from which I have extracted x,y positions of the coordiates of labelled cells exported from ImageJ as a.csv file. I also have images that define an underlying pattern in the tissue defined as areas of different pixel values 0 or 255 (also 512x512) I've exported these images as .txt

Hi all ! I'm new in this list and newbie about R I'm trying to use R scripts (as in the attached file) for creating some distributions plots of data retrieved by a workflow(with Rserve, to be precise). I was able to do it (even if not in a beatiful way, I have to improve it especially about labels and coordinates) with number inputs like :

Hi: The gls function I used in my code is the following fm<-gls(y~x,correlation=corARMA(p=2) ) My question is how to extact the AR(2) parameters from "fm". The object "fm" is the following. How can I extract the correlation parameters Phi1 and Phi2 from "fm"? These two parametrs is not in the "coef" componenet of "fm". Thanks a

I did an svn up this morning and discovered this whole new bundle of code! Lookingn through it it looks cool, but there''s no CVS support for an SCM - I''d have thought this would be more widely used than darcs. Looking at the code for subversion.rb and I thought it''d be possible to add a new scm - CVS. I''m running into 3 problems: 1- I''m still

Dear R forum I have data.frame as df = data.frame(rate_name = c("USD_1w", "USD_1w", "USD_1w", "USD_1w", "USD_1m", "USD_1m", "USD_1m", "USD_1m", "USD_2m", "USD_2m", "USD_2m", "USD_2m",  "GBP_1w", "GBP_1w", "GBP_1w", "GBP_1w",

We are trying to use the corCompSymm function in nlme The example from the help pages for the corAR1 function gives the following > corAR1(0.2, form = ~ 1 | Mare) Correlation structure of class corAR1 representing Phi 0.2 We are expecting a somewhat similar correlation specification with the help page example for corCompSymm, but just get an error instead > corCompSymm(0.5, form = ~ 1 |