similar to: singular variance-covariance warning in lmer

On starting an R session, I get the messages: Fatal errir: unable to restore save data in .RData Error in fun(...): couldn't find function "assignInNamespace" Error: .onLoad failed in 'loadNamespace' for 'Matrix' The only object in my .RData is last.warning, thus: > last.warning $"optim or nlminb returned message false convergence (8)"

Dear all I want to compute Monte Carlo p-values in lmer-models based on sampled data sets. To speed up calculations, I've tried to use internal functions from the Matrix package (as suggested ealier on the list by Doug Bates). So I did: fm2 <- lmer(resistance ~ ET + position + (1|Grp), Semiconductor,method='ML') simdata<-simulate(fm2,nsim=1) ynew <- simdata[,1] mer

Hi - I am doing some monte carlo simulations comparing bayesian (using Plummer's jags) and maximum likelihood (using lmer from package lme4 by Bates et al). I would like to know if there is a way I can flag nonconvergence and exceptions. Currently the simulations just stop and the output reads things like: Error in optim(.Call("lmer_coef", x, 2, PACKAGE = "Matrix"), fn,

i use library(ncdf) to read this file as follow library(ncdf) sst.nc = open.ncdf(title) lonall = get.var.ncdf(sst.nc,'lon') latall = get.var.ncdf(sst.nc,'lat') precip = get.var.ncdf(sst.nc,'pre') close(sst.nc) if i use this method my pc freeze and not respond until i restart it is there -- View this message in context:

Hi, I am fitting a weighted least square regression and trying to compute SSE,SST and SSReg but I am not getting SST = SSReg + SSE and I dont know what I am coding wrong. Can you help please? xnam <-colnames(X) # colnames Design Matrix fmla1 <- as.formula(paste("Y ~",paste(xnam, collapse=

Dear RUsers, I guess this is an easy question for someone a little familiar with programming...(which I am not)... I've got 2 colummns, one shows just dates(SST_date, Class 'Date' num), the other one shows the SeaSurfaceTemperature (SST, num) at that certain date. SST_date SST 2008-01-01 22.2 2008-01-02 21.8 2008-01-03 22.8 2008-01-04 22.9 2008-01-05 23.1 2008-01-06 23.2 ...

Hello I am a new user of R . and I ve problem with R and netcdf . I succed installation , I could use all examples . But when I take my netcf it is different . I want to do statistic on this kind of file . 1) first calculate mean . my data is like that through ncdump -h test.nc netcdf test { dimensions: lat = 301 ; lon = 401 ; time = UNLIMITED ; // (80 currently)

Hello, This is probably very simple but I am trying to select a region from the OIv2 SST dataset that crosses 0 longitude. The longitude variable is arranged from 0 to 360 and I get an error message when trying to go from 330 to 30 for example. The data are from a NOAA netCDF file. *temp = open.ncdf("c:/documents and settings/theoni/desktop/sstoi_v2.nc") print(temp) y1 = get.var.ncdf(

Hi- I'm wrestling with some of my data apparently not being called into a GLM or an LM. I'm looking at factors affecting fish annual catch rates (ie. CPUE) over 30 years. Two of the factors I'm using are sea surface temperature and sea surface temperature anomaly. A small sample of my data is below: CPUE Year Vessel_ID Base_Port Boat_Lgth Planing SST Anomaly 0.127

Dear all, I am analyzing some data that requires a mixed model. I have been reading Pinheiro and Bates' book, but cannot find the notation to fit the following model: Suppose I have the dataset below. Here I am fitting variable p as a fixed effect, variable h as a random effect and variable t as nested within h. I would like to include the variable j as well as an independent (non-nested)

Hi, I'd like to compare SST data for year 2000 with SST for year 2001. I managed to get filled contour plots showing monthly SST for both years (12 plots for each year, 24 plots in total). In order to compare year 2000 and year 2001, however, I'd need to have the same legend scale (same color bar) in both years plots. Thus, my question is: is there a way to set the legend scale in

Hi, I have been working with R for the last year and using the UKFSST package to look at satellite tag track data and SST information. Fpr those not familiar, the package uses the positions estimated by the satellite tags themselves and the associated SST data from servers (in this case, from the University of Hawaii and the NOAA Coastwatch website) for the time preiod to estimate a reasonable

Hi, I am looking at the effects of two explanatory variables on chlorophyll. The data are an annual time-series (so are autocorrelated) and the relationships are non-linear. I want to account for autocorrelation in my model. The model I am trying to use is this: Library(mgcv) gam1 <-gam(Chl~s(wintersecchi)+s(SST),family=gaussian, na.action=na.omit, correlation=corAR1(form =~

Hi, I have a problem with the appearance of legend in my plots. If I specify the legend positions in characters like "topright"..etc, it appears, if i specify it in terms of coordinates like "-1, 1" .. etc, it does not appear. Can anyone help me with this? script - x.date <- as.Date(paste(year, month, day, sep="-")) ts1.n.e3 <- ts(data.nemr.e3[,3]) z1.n.e3

Hi: I'm using function lmer from package lme4, and I get this message: " There were 12 warnings (use warnings() to see them)" So I checked them: Warnings 1 to 11 said: 1: optim returned message ERROR: ABNORMAL_TERMINATION_IN_LNSRCH in: "LMEoptimize<-"(`*tmp*`, value = structure(list(maxIter = 50, ... and Warning 12 said: 12: IRLS iterations for glmm did

This concerns whether p-values from lmer can be trusted. From simulations, it seems that lmer can produce very small, and probably spurious, p-values. I realize that lmer is not yet a finished product. Is it likely that the problem will be fixed in a future release of the lme4 package? Using simulated data for a quite standard mixed-model anova (a balanced two-way design; see code for the

Hi everyone, My background is not math and I am trying to figure out exactly what equation to use to map a response variable in GIS based on the coefficients obtained from the GLM and the values of the independent variables in each grid cell of my study area. Most specifically, I want to know how to incorporate the Poisson family and log link function in the equation. I would really appreciate if

Dear Mac users, Hi, as you might have probably read the thread of "[R] Rsquared in summary(lm)" on May 10, it seems that Mac version of lm() seem to be working incorrectly. I enclose the script to produce the result both for lm() and manual calculation for a simple regression. Could you run the script and report with the version of R, so I don't have to go through every builds

Hi, I seem to be having a problem adding the following two raster objects together - one is a rasterLayer, the other is a rasterBrick. The extent, resolution, and origin are the same, so according to my understand it should work. The objects look like so: > obs.clim class : RasterLayer dimensions : 60, 200, 12000 (nrow, ncol, ncell) resolution : 0.5, 0.5 (x, y) extent : -70,

Hello, everyone, I'm using R to deal with a REML problem. I found "lmer" is the right function for this. But I got stuck because I couldn't interpret the result. I'm attaching a short example of my executing log. Please have a look and give me some advice on it. Thanks a lot! Plot Block Treatment Data 1 1 2 7.8 2 1 1