similar to: Specifying spatial correlation Form in nmle

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

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

Hi: First my apologies for cross-posting. A few days back I posted my queries ar R-sig-geo but did not get any response. Hence this post. I am working on two parcel-level housing dataset to estimate the impact of various variables on home sale prices. I created the spatial weight metrics in ArcGIS 10 using sale year of four nearest houses to assign weights.  Next, I ran LM tests and then ran

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:

Dear R users, I'm estimating a mixed effects model in which the spatial correlation is controlled for by the "corGaus" structure. I'm wondering if there is a document or paper that explains how the spatial correlation structure (such as "corExp" or "corGaus") works. Let me use the example and data posted on UCLA's R FAQ webpage to explain my problems.

[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

Dear listers, I am trying to model the distribution of fox density over years in the Doubs department. Measurements have been taken on 470 plots in March each year and georeferenced. Average density is supposed to be different each year. In a first approach, I would like to use a general model of this type, taking spatial correlation into account:

Like Tomas, I find the paste0 readability to be **much** better, partly because it allows for better indentation (as Tomas pointed out). Perhaps a pointless email, but sometimes - for these subjective issues - it is worthwhile to point out a difference in opinion. Best, Kasper On Mon, Jun 2, 2025 at 12:27?PM Tomas Kalibera <tomas.kalibera at gmail.com> wrote: > > On 6/2/25 17:37,

Hi I am using R 1.7.1 on RH linux 9.0 > sum(unlist(lapply(ls(),function(x)object.size(get(x)))))/1024^2 [1] 2.424263 so I am not using much memory (I have a gig of ram on my machine) now in nlme > gtest<-groupedData(log(X8)~Time|sub,all[,c(names(all)[1:9],"X8")],outer=~A*B) > object.size(gtest)/1024 [1] 59.98438 > plot(gtest,outer=~Dose*chem,key=FALSE,asp=.5) Plotting

Following the Indomethicin example in Pinheiro & Bates, chapter 6, page 277 etc, coming to the following comand: fm2Indom.nlme <- update( fm1Indom.nlme, random = pdDiag(A1 + lrc1 + A2 ~ 1) ) debugging nlme gives the following output: Browse[1]> n debug: modelResid <- ~eval(model, data.frame(data, getParsNlme(plist, fmap, rmapRel, bmap, groups, beta, bvec, b, level,

Hello. I have 16 subjects with 1-4 obs per subject. I am using the package "nlme" to fit a simple random effects (variance components model) with 3 parameters: overall mean (fixed effect), between subject variance (random) and within subject variance (random). I need a 3x3 variance-covariance matrix that includes all 3 parameters in order to compute the variance of a specific

Hi, All: Does 'nlme' require the nonlinear function to be differentiable? I'm fitting structural change models to many related time series, and I'd like to improve the estimates of the change point times through some type of pooling. Unfortunately, I've so far been unable to get 'nlme' to work for me. The following toy example is the closest I've come

A few days ago I posted a question to this discussion group concerning to origin of an error message < subscript out of bounds > while using the nonlinear mixed model (nlme) function in R with a self-starting function. Thanks for those who responded. This posting is to explain what (I think) it causing the error. Pinheiro & Bates (2000, pages 342-347) describe how to construct a

Hi, I am not sure this is a bug but I can repeat it, The functions and data are below. I know this is nasty data, and it is very questionable whether a 4pl model is appropriate, but it is data fed to an automated tool and I would have hoped for an error. Does this repeat for anyone else? My details: > version _ platform i686-pc-linux-gnu

On 6/2/25 17:37, Josiah Parry wrote: > Tomas, > > Here is a good example of where this functionality would be useful: > https://github.com/R-ArcGIS/arcgislayers/blob/2b29f4c254e7e5a1dadce8d4b0015a70dfae39d4/R/arc-open.R#L19-L56 > > In order to prevent R CMD check notes I have to use `paste0()` to > concatenate long URLs. If we were able to use `\` to > separate the string

Dear all, I have been using the function gls in the package nlme in R to fit some spatial regressions (as described in Dormann et al.). However, I have been struggling trying to find a way to calculate a measure of effect size from these models, so I wanted to know if any of you had an idea on how to do this. More precisely, I am producing a multiple model with an exponential correlation

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.

One could also argue that paste0("a", "b", "c") is a function call that needs to be evaluated at runtime, whereas "abc" is a string constant understood by the parser, and often also language agnostic. I'd assume compilers and code- and text-search tools do a better job with the latter. /Henrik On Mon, Jun 2, 2025 at 2:18?PM Josiah Parry

I suppose taste is learned as well. It does feel quite odd that the best way to define a long string without a note or text wrapping is by being creative with functions. This is valid in Python, Julia, and Rust (if you add `let` and a terminating semi-colon): my_str = "part1\ part2\ part2" I don't think it is abnormal to expect or desire this type of functionality in our favorite

Dear all, I am experiencing problems using the glmmPQL function in the MASS package (Venables & Ripley 2002) to model binomial data with spatial autocorrelation. My question - is the presence of birds affected by various hydrological parameters? Presence/absence data were collected from 83 sites and coupled against hydrological data from the same site. The bird survey sampling effort