search for: likfit

> -----Original Message----- > From: r-help-bounces at stat.math.ethz.ch [SMTP:r-help-bounces at stat.math.ethz.ch] On Behalf Of ernesto > Sent: Friday, January 13, 2006 9:25 AM > To: Mailing List R > Subject: [R] help with gepRglm::likfit.glsm > > Hi, > > I'm exploring likfit.glsm and I need some help. I have to say that I'm > not an MCMC expert ... > > I did a first run of likfit.glsm with S.scale=0.002 and it worked > whithout problems but there was strong autocorrelation and the chain > conve...

Hi I'm using geoR package to perform linear spatial interpolation(OK). The function likfit() fails to compute REML. The error meassage is : Error in solve.default(v$varcov, xmat); How I can find out that likfit() is failed to process and retrieving the error message ? Thank you so much for your help.

ComRades: I am geeting the error message Error in ldots[[which(MET)]] : attempt to select less than one element when I try to fit the geostatistical model with the likfit() function of geoR. I have tried with old data for which likfit() successfully maximised the likelihood in previous versions of geoR, and yet the current version fails. I have tried in Windows Vista and Windows XP (I haven't tried in Linux systems) and the problem occurs in both systems. Below...

We want to compute a pseudo R-squared for a model whose parameter estimation was based on maximum likelihood (function likfit, package geoR). I tried to compute the R2 proposed by Maddala (1983) which compare the maximized likelihood for the model without any predictor and the maximized likelihood for the model with all predictors. I got a really low value (0,01%). Did I miss something? Are there other R-squared which...

Mzabalazo Ngwenya wrote: > Hi everyone ! > > I'm am trying to fit a kriging model to a set of data. When I just run > the "likfit" command I can obtain the results. However when I try to > pass additional arguements to the optimization function "optim" I get > errors. That is I want to obtain the hessian matrix so matrix > (hessian=TRUE). > > Heres a little example( 1-D). Can anyone shed som...

...low: / model.5 = list(cov.pars=c(1,1), cov.model='exponential', beta=1, family="poisson") mcmc.5 = mcmc.control(S.scale = 0.25, n.iter = 30000, burn.in=50000, thin = 100) #trial error outmcmc.5 = glsm.mcmc(geoData9093, model= model.5, mcmc.input = mcmc.5) mcmcobj.5 = prepare.likfit.glsm(outmcmc.5) lik.5 = likfit.glsm(mcmcobj.5, ini.phi = 0.3, fix.nugget.rel = F)/ And the summary of lik.5 is: likfit.glsm: estimated model parameters: beta sigmasq phi tausq.rel "1.2781" "0.5193" "0.0977" "0.0069" likfit.glsm : max...

Hi everyone !   I'm am trying to fit a kriging model to a set of data. When I just run the "likfit" command I can obtain the results. However when I try to pass additional arguements to the optimization function "optim" I get errors. That is I want to obtain the hessian matrix so matrix (hessian=TRUE).   Heres a little example( 1-D). Can anyone shed some light?  Where am I going w...

I have been modelling spatial data using function likfit in package geoR. Now that I have the spatial regression models, I would like to calculate the amount of variance explained by both the trend and the spatial parts of the model. Any advice on how to do this would be much appreciated. Cheers, Ailsa

Greetings comRades: Has anyone worked out a procedure to calculate the estimated covariance between the beta and lambda estimates in the likelihood-based geostatistical model implemented in package geoR? If so, please help me out by letting me know. Do I have reasons to expect that this covariance term would be big or perhaps more happily, that it could be discarded without much effect?

...I can get data summaries by realisation from the geodata object.) However, after reading the packages' documentation and searching the mailing lists and other sources, it seems that the functions in geoRglm do not acknowledge the existence of multiple realisations per site. I see that the likfit() function in geoR has an argument for realisations, but I cannot find anything similar in geoRglm. Is it possible to model data with repeated realisations from the same sites using geoRglm? If so, how can this be done and is there a way to model dependence among the realisations over time?...

Hola, LLevo buscando desde hace tiempo como hacer el Goodness of fit test en R. Es decir, me explico, intento hacer una cosa parecida que se hace en Minitab, por ejemplo, yo tengo un conjunto de datos, y lo que quiero es sabes que tipo de distibución es, en minitab se hace un histograma para ver si se ajusta bien o no a la campana de Gauss, luego vemos si aproximar la distribución de la muestra

Hi I am struggling to fit a non-linear trend using the likfit function in geoR. Specifically I want a sigmoidal function, something like SSfpl in the nls package to fit the trend. But it seems trend.spatial in geoR only works with lm or glm type models. Any ideas how I can specify the model to calculate the kriging parameters using REML, including the para...

Hi, I want to automatically fit variograms to a large number of different sample data sets, and call the funtion "likfit" (in package geoR) from within a for-loop. "likfit" does again call "optim". After ssuccessfully fitting variograms to some of the data sets, the procedure crashes and I get the error message: Error in optim(par = ini, fn = negloglik.GRF, method = "L-BFGS-B",...

...imal cutpoint based on deviance measures obtained from likelihood estiamtes. This is in the geo-spatial context so I'm actually using the geoRglm package to obtain this likelihood fit. I initially use the "variog" function to help specify the initial parameter values passed to "likfit" to ensure convergence. Although not the most elegant solution, the code works ... I just want to re-code it to avoid using the "for" loop. Any help would be greatly appreciated. This is what I've got .... RootDev <- 600 splits <- NULL for (cutpoint in cutpoints) {...

Hello, I used glsm.mcmc and likfit.glsm to create model. Now I want to predict at different locations, but I can't get glsm.krige to work. I keep getting the error that trend.d and trend.l must have similar specifications. I have tried numerous ways to include the covariates in the glsm.krige model, and I keep getting the same e...

I am having difficulty getting the trend.spatial function in geoR to work properly. After creating a trend.spatial object with a covariate, I try to add the command into my likfit() function as follows: trend1.trend.spatial <- trend.spatial("1st", trend1.geodata) trend1.spatial.EC0.1.reml <- likfit(spatial.geodata, trend1.trend.spatial, ini.cov.pars = spatial.EC0.1.eyefit, fix.kappa = FALSE, fix.psiA = FALSE, fix.psiR = FALSE, + lik.method = "REM...

Hi, R-folks: I have been tryin many combination of parameter to make Matern variogram to work, but I can't find the available one. I'm near to be crazy. I tiped: A?o2003Selg.lf<-likfit(A?o2003Selg,cov.model="matern",ini.cov.pars=c(1.5,14),kappa=2.5,fix.kappa=FALSE,nugget=0.08,lambda=0.008,fix.lambda=FALSE,hessian=TRUE) the hessian shows: $hessian [,1] [,2] [,3] [,4] [1,] 9.139986 -8.562736e+00 41.648355 -3.801615 [2,] -8.562736 3...

All, I am new to using R and know some basics. I wish to use kriging in R to do the following: given data Y =f(X1,X2,X3,.....,Xn) --1000+ irregular measured data set. I would like to be able to get a single value y given sinle input set (x1,x2,x3,...xn) A google search on this takes me lierally to the same example on involving analysis with soil sampling and I cannot figure out how to

...trix yourself from the coordinates file (but you may meet meory problem anyway). Still more straigthfully, if you intend to use interpolation methods such as kriging, you don't need to manage the distance matrix building by yourself. See: library(geoR) library(help=geoR) ?variog ?variofit ?likfit? etc... If you want further use geostatics (eg via geoR or gstat), you will anyway have to manage with memory limits (not due to R). On my computer (portable HP compaq nx7000) I can hardly manage with more than 2000 observations using geoR (far from your 18227 observations). I had to krige on...

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