similar to: Struggeling with nlminb...

Hallo together, I am trying to use the nmkb() optimizer and I have problems using the function, as it causes the following error message Fehler (error)* in while (nf < maxfeval & restarts < restarts.max & dist > ftol & : Fehlender Wert (missing value)* , wo (where)* TRUE/FALSE n?tig ist (is required)* *translation Do I need to adjust the control ?

Dear R help list, I have a plot with two different vertical scales that I want to display on either side of the plot. It's quite similar to the Fahrenheit-Centigrade example in the examples section of the documentation for axis.default. The right-side axis is clipped off, though, and I haven't been able to figure out anything with viewport() and clipping or trellis.par.set to fix

Dear all, We are analysing some survey data and we are not sure if we are using the correct syntax for our design. The population of interest is a set of 4416 polygons with different sizes ranging from 0.003 to 45.6 ha, 7460 ha in total. Each polygon has a binary attribute (presence/absence) and we want to estimate the probability of presence in the population. We used sampling with replacement

Hi, I got the same problem like http://tolstoy.newcastle.edu.au/R/devel/04/11/1204.html R crashes when I use the em function from the mclust package on univariate data and on a special case on bivariate data (when the matrix is not provided as written in the manual). It seems as if the problem is the format of the data to be analyzed. Operating System: Windows XP (SP2) R version: R-2.0.1 The

I'm applying a function (Cov.f) defined below to each element of a distance matrix. When I run the code below, I get a warning message (below) and elements of returned matrix [2,3] and [3,2] are not zero as I would expect. Clearly, there is an error... What am I doing wrong? Thanks. --Dale Warning message: In if (h <= phi) { : the condition has length > 1 and only the first element

Hi, I am trying to run th mclust package on a variable "Tuberculin indurations" recorded as mm. The file has only one variable. When I run the package I get NULL value for mu and sigma. Can anybody say why? This is the program: library("mclust") mc<-Mclust(x.trab,G=1:9,warn=TRUE) mc mc$mu sqrt(mc$sigmasq) and the output I get is > library("mclust")

Dear Knowledgeable R Community Members, Please excuse my ignorance, I apologize in advance if this is an easy question, but I am a bit stumped and could use a little guidance. I have a finite mixture modeling problem -- for example, a 2-component gaussian mixture -- where the components have a large overlap, and I am trying to use the "mclust" package to solve this problem. I need

Dear people, I've a problem in doing a power calculation. In Fryer and Nicholson (1993), ICES J. mar. Sci. 50: 161-168 page 164 an example is given with the following characteristics T=5, points in time R=5, replicates Var.within=0.1 q=10, a 10% increase per year The degrees of freedom for the test are calculated as Vl=T*R-2=23 and the non-centrality parameter Dl=4.54. Using this they get a

A majority of my data makes a kriged map perfectly using an exponential model for the semivariogram to fit my data and then going through the commands variofit() to define the model and then krige.conv() to use the model to predict values in a grid. But?one set of my data appears to be linearly correlated for the first 5000 meters and not correlated beyond that. I have been having problems

Dear Knowledgeable R Community Members, Please excuse my ignorance -- I apologize in advance if this is an easy question, but I am a bit stumped and could use a little guidance regarding parameters in 2 functions in the "mclust" package. -------------------- PROBLEM DESCRIPTION -------------------- I have a finite mixture modeling problem -- for example, a 2-component gaussian

Hello, I am writing an extension that requires the user to pass a function into the C code. The function returns a covariance matrix. The user defines an arbitrary set of parameters as the function's arguments, which are used to construct this covariance matrix. Within the C code these parameters and hence covariance matrix are iteratively updated. The user's function might look like

I keep on receiving the message below after submitting the following line using the mclust package. m2 is a 99 X 1 column vector. * em(modelName = "E", m2, mu = c(25, 50), sigmasq=10, pro = c(0.4, 0.6)) Error in as.double.default(data) : (list) object cannot be coerced to double. Why do I receive this error? Thank, Brian C. Newquist Research Statistician

Whenever I submit the following command >result <- em("E", m1, mu=c(25, 50), sigmasq=10, pro=c(0.49,0.51)) in MCLUST , I experience a problem with my Windows XP. Has anyone had this type of problem? I receive the general "send report" dialogue box and my program is no longer able to run. Should I change any of my system settings? Let me know if you think of anything

Dear R users. I'm trying to fit a generalised linear spatial mode using the geoRglm package. To do so, I'm preparing my data (geodata) as follow: geoData9093 = as.geodata(data9093, coords.col= 17:18, data.col=15,* covar.col=16*) where covar.col is a factor variable (years in this case 90-91-92-93)). Then I run the model as follow: / model.5 = list(cov.pars=c(1,1),

Hi Everybody, Thanks in advance for your help. This is my first time using the foreach statement and I cant get it to work properly so here is what i have test<-function(){ repeat { cand2[l-1]<-rinvgamma(1,phi,lambda[l-1]) q2<-dinvgamma(cand2[l-1],phi,lambda[l-1]) p2<-cand2[l-1]^-1.5*exp(-y[l]^2/(2*cand2[l-1]))*exp(-((log(cand2[l-1])-mu_t_cand[l-1])^2)/2*sigmasq)

> No HTML this time. Sorry Dear all, I am attempting to model some one-dimensional data using Gaussian mixture model with mclust.? Generally, the data that I have have 3 overlapping populations (with one of them being the majority, and the other two combining to less than 15%) and for some reason, mclust consistently ignores the smaller peaks, giving me strange values for the means

Dear all I have a problem in fitting lines() of the normal distributions identified with Mclust on a histogram or a mclust1Dplot. Here is some sample code to explain : set.seed(22) foo <- c(rnorm(400, 10, 2), rnorm(500, 17, 4)) mcl <- Mclust(foo, G=2) mcl.sd <- sqrt(mcl$parameters$variance$sigmasq) mcl.size <- c(length(mcl$classification[mcl$classification==2]),

Hi R people: I am new to R. I am writing a function to (1) produce a sparse stochastic Gaussian 2D field and (2) perform a systematic transect sampling on this field, this carried out many times in a simulation framework. My function does a good job at producing the random field (a matrix of zeros and some manifestations of the stochastic process, depending on a parameter of the function

Dear all, I am attempting to model some one-dimensional data using Gaussian mixture model with mclust. Generally, the data that I have have 3 overlapping populations (with one of them being the majority, and the other two combining to less than 15%) and for some reason, mclust consistently ignores the smaller peaks, giving me strange values for the means (completely anti-intuitive in terms of

Hi cross posting from sig geo , because I really need help! I'm using geoR for some spatial linear models and I'm getting surprisingly optimistic values from the spatial models relative to the non-spatial, even when the models appear to be performing about equally (by AIC comparison) For example This model relating encounter rates of lizards to a soil substrate parameter gives >