similar to: nlme: correlation structure in gls and zero distance

Hello, I am having a problem specifying the correlation structure in lme which leads to the error: Error in getCovariate.corSpatial(object, data = data) : Cannot have zero distances in "corSpatial". I have specified a grouping variable which is the only fix I could find by searching this error on R-help. ISee the below example. When my samples (tran) - which are transects

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

I noticed that ?corClasses in package nlme does not list corSpatial among the standard classes. This might either be intentional because corSpatial is not "standard" , or it might be simply an oversight that needs correcting. ------------------------------------------ Robert W. Baer, Ph.D. Professor of Physiology Kirksville College of Osteopathic Medicine A. T. Still University of

I have spatial data on a sphere (the Earth) for which I would like to run an gls model assuming that the errors are autcorrelated, i.e. including a corSpatial correlation in the model specification. In this case the distance metric should be calculated on the sphere, therefore metric = "euclidean" in (for example) corSpher would be incorrect. I would be grateful for help on how to

I'd like to compare two models which were fitted using gls, however I'm having trouble interpreting the results of gls. If any of you could offer me some advice, I'd greatly appreciate it. Short explanation of models: These two models have the same fixed-effects structure (two independent, linear effects), and differ only in that the second model includes a corExp structure for

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.

[I think I've seen this reported before but can't locate it any more. I believe this oddity (glitch? feature?) is behind a query that Jean-Baptiste Ferdy asked a year ago <http://finzi.psych.upenn.edu/Rhelp08/2008-October/176449.html>] It appears that glmmPQL looks in the global workspace, not within the data frame specified by the "data" argument, for the variables

Hope one of you could help with the following question/problem: We would like to explain the spatial distribution of juvenile fish. We have 2135 records, from 75 vessels (code_tripnr) and 7 to 39 observations for each vessel, hence the random effect for code_tripnr. The offset (‘offsetter’) accounts for the haul duration and sub sampling factor. There are no extreme outliers in lat/lon. The model

Hi, I am trying to place my own functions in the nlme environment: The following statement works: environment(coef.corSPT) <- environment(getS3method("coef","corSpatial")) but this one returns an error: environment(get("coef<-.corSPT")) <- environment(getS3method("coef<-","corSpatial")) Error in

Hello, we've been using dovecot for pop3 and imap for some time now and we're in the middle of deploying lmtp as well, however we're run into a problem we can't solve. Specifically for some reason it seems that dovecot tries to write to the wrong index file during some, but not all, lmtp deliveries. If lmtp tries to deliver to person user_a at domain, sometimes it'll try to

This is somewhat a reincarnation of a problem I am facing since upgrading to samba 3.5.6 (3.5.8 is identical). I use samba on an ext3 ACL enabled file system. Typically a users access rights are determined by his or her membership in different groups. The access right is therefore defined and granted by/to the group, not the user. These groups then appear in the ACL of directories and files

I am having trouble fitting correlation structures within nlme. I would like to fit corCAR1, corGaus and corExp correlation structures to my data. I either get the error "step halving reduced below minimum in pnls step" or alternatively R crashes. My dataset is similar to the CO2 example in the nlme package. The one major difference is that in my case the 'conc' steps are

Hi all, I wrote a piece of code that generates simulated variables. after variable generation I use them in several analyzes. However, when I use a for to repeat the procedure 1000 times I get an erro message in one of the "for" steps, precisely at this time: gls.temp<- gls(y2 ~ x2,correlation=corExp(form=~coord2[,1]+coord2[,2])) # coord 2 are spatial coordinates and the error

Hi all, I have been attempting this repeated measure analysis where correlation among observations (within each subject) is spatial. My command is: >fdat.lme1<-lme(Lint~Rep+Treatment,data=fdat,random=~1|fldPos,correlation=corLin(form=~lat+lon)) It is generating follwoing error: Error in getCovariate.corSpatial(object, data = data) : Cannot have zero distances in "corSpatial"

Hello, I'm using a flash player. First It didn't work with icecast 2. The blocking difference between icecast 1 and icecast 2 is that icecast 2 don't send the Content-Length header. So, I made a small PHP proxy and now Flash works very well with icecast 2. Other solution is to add this header in the icecast 2 source code and compile it, but I don't have time to test. My

Hi, I'm trying to introduce a (spatial) exponential correlation structure (with range=200 and nugget.effet of 0.3) in a lme model of this form: lme(ARBUS~YEAR, random=~1|IDSOUS). The structure of the data is "IDSOUS" "XMIN" "YMAX" "YEAR" "ARBUS" with 2 years of data and 5600 points for each year. I do:

  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

Hello, I have been asked to perform a exponential correlation on a data set. Unfortunately, i did not find any simple example on how to do that with R. If the correlation is significant, one asked me to also find the thresold of the acceleration slope. Have any of you a little example or a good link to get me started? Best regards Blaise -- Mutt, c'est de la balle, quand ??a marche :-)

Dear R helpers, I would like to model temporal trend of biological remains in sediment cores. All samples are temporally auto-correlated and I would like to take this effect into account. Initially I thought that I could use AR(1) or ARIMA functions but these functions only work with regular temporal intervals between samples. Hence I would like to use a continuous time AR(1) that allow

>>>>> "VW" == Viechtbauer Wolfgang (STAT) <Wolfgang.Viechtbauer at STAT.unimaas.nl> >>>>> on Fri, 26 Sep 2008 18:00:19 +0200 writes: VW> Hi all, I'm trying to fit a marginal (longitudinal) VW> model with an exponential serial correlation function to VW> the Orange tree data set. However, R crashes frequently VW>