similar to: Simon Wood GAMsetup

Hello, someone knows which function has replaced the GamSetup function in mgcv? With R 1.6 version we have GamSetup but this function doesn't exist with R 2.7.2 version [[alternative HTML version deleted]]

? stato filtrato un testo allegato il cui set di caratteri non era indicato... Nome: non disponibile Url: https://stat.ethz.ch/pipermail/r-help/attachments/20060627/84d9bd54/attachment.pl

My name is Michela Marignani and I'm an ecologist trying to solve a problem linked to knight' s tour algorithm. I need a program to create random matrices with presence/absence (i.e. 1,0 values), with defined colums and rows sums, to create null models for statistical comparison of species distribution phenomena. I've seen on the web many solutions of the problem, but none provides

Hi, can you tel me how can I make a Forrest Plot with R? It is possible and easy or are there a more practical free software available? Than you Mic [[alternative HTML version deleted]]

Dear R-Users, I have a model with a latent variable for a spatio-temporal process. I would like to use EM algorithm to estimate the parameters. Does anybody know how to implement the algorithm in R? Thank you very much in advance, Michela

Dear R users, we are trying to do some parallel computing using library(snow). In particular we have a cluster with 3 nodes >cl <- makeCluster(3, type = "MPI") 3 slaves are spawned successfully. 0 failed. and we want to compute the function op_mat (see below) first with the master and then with the cluster using system.time for checking the computational performance.

Dear R-Help Members, I am trying to read and analyse a set of 100 csv files. I need work only on some columns in each of those, so I decided to use a for loop, isolate the column in each file to work on, but then an error mesage appear: "undefined columns selected" Here is my code: setwd("F:/Data/") a<-list.files() for (x in a) { ? u<-read.csv(x, header=T,

Dear R-users, we are using library(snow) for computation on a linux cluster with RMPI. We have a problem with clusterEvalQ: after launching clusterEvalQ it seems loading the required library on each node but if we type a function belonging to the loaded package R doesn't find it. > library(snow) # making cluster with 3 nodes > cl <- makeCluster(3, type = "MPI") Loading

Hello, I write to know how can I modify the x axis : when I plot a survival object, R plots a graph with x values = 0, 10, 20, 30 while I want a graph with values 0, 6, 12, 18, 24 in the x axis. How can I do this? In R 2.1.1 version there was "time.inc" in survplot, but in version R 2.2.0 there isn't it! I am sorry for my english and I hope that you understand my problem. Thank you

Dear R user, I'm trying to find a solution for optimizing my code. I have to run a 50.000 iteration long simulation and it is absolutely necessary to have an optimized code. I have to do this operation *sum_t ( t(X_t) %*% A %*% X_t )* where X_t is a (d*k) matrix which changes in time and A is a constant in time (d*d) matrix. I have put all my X_t in a three dimensional array X of dimension

I'm looking for the best way to do the following: run a set of GAM models, and then make predictions with new data. My problem is the size of the gam model object, I would like to strip it down to the bare minimum of information needed to apply the model to new data. For example, if this were a linear model, I would just keep the betas. If this were an ordinary spline fit, I think I

I'm fitting a Poisson gam model, say model<-gam(a65tm~as.factor(day.week )+as.factor(week)+offset(log(pop65))+s(time,k=10,bs="cr",fx=FALSE,by=NA,m=1),sp=c( 0.001),data=dati1,family=poisson) Currently I've difficulties in obtaining right predictions by using gam.predict function with MGCV package in R version 2.2.1 (see below my syntax).

Dear R-users, I have a little problem that I can't solve by myself. I have a data frame with 2 factors and 8 observations (see the following code): y <- c(1,1,1,2,2,3,3,3) y <- factor(y) levels(y) <- c("a","b","c") x <- c(1,2,3,1,2,1,2,3) x <- factor(x) levels(x) <- c("x","y","z") X <-

Hi everybody, I'm a beginner in R and I'm having a hard time grouping my data by day. The data are in this format: id; words 2005-07-07T09:59:56Z; 35 2005-07-07T10:01:39Z; 13 2005-07-08T10:02:22Z; 1 2005-07-09T10:03:16Z; 23 2005-07-10T10:04:23Z; 39 2005-07-10T10:04:39Z; 15 I've transformed the date strings in dates with the function: london$id <- transform(london$id,

Dear R-Users, I'm using SSPIR package for a spatio-temporal application. Is it possible to modify the structure of the involved matrixes (Fmat, Gmat, Vmat,Wmat)? I want to create a model like this #y(t)=k*theta(t)+epsilon(t) #theta(t)=h*theta(t-1)+eta(t) #epsilon(t) N(0,V) V=sigma2*I #eta(t) N(0,W) W=sigma2_eta where the state variable theta has dimension 1(p=1) and at

Hi all, I'm using RScalapack library for parallelizing some heavy matrix operations required by MCMC methods for spatio-temporal models. The package reference manuals (dated 2005) states that the library needs LamMPI to work but we have a Linux Cluster with OpenMPI. We have found (http://cvs.fedoraproject.org/viewvc/devel/R-RScaLAPACK/) a patch for OpenMPI but we are wondering if in the

Hello: I sent this question the other day with the wrong subject heading and couple typos, with no response. So, here I go again, having made those corrections. I would like to estimate, for lack of a better description, a partially additive non-parametric model with the following structure: z~ f(x,y):w1 + g(x,y):w2 + e In other words, I'd like to estimate the marginals with respect to

Dear R users, we are trying to build a R package that includes a precompiled shared library, let's say mylib.so. We created the skeleton of the package and we moved the mylib.so file into the libs folder that we created at the same level of the folders man and R. Moreover we created the file NAMESPACE and we added the line useDynLib(mylib, .registration=TRUE). The building step seems to work

Dear R users, Using the library(mgcv) and running R under MacOSX, I have fitted a generalised additive model with binomial errors in order to check the linearity of two continuous variables ap2mm and diffdaysm in a glm: > mymodel.gam <- gam(diedhos~ s(ap2mm) + Dweekm + s(diffdaysm) + Dweekm:diffdaysm + ap2mm:Dweekm, binomial) I would like postscript gam plots for the two smoothed

Hello, I write to know how can I modify the x axis : when I plot a survival object, R plots a graph with x values = 0, 10, 20, 30 while I want a graph with values 0, 6, 12, 18, 24 in the x axis. How can I do this? In R 2.1.1 version there was "time.inc" in survplot, but in version R 2.2.0 there isn't it! I am sorry for my english and I hope that you understand my problem. Thank you