similar to: EM algorithm

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-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

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

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 <-

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

Dear R-helpers, I have 4-dimensional atmospheric data (x,y,z,t), which I want to analyse on spatio-temporal diversities. As far as I understand there only exists the possibility to construct time series as two-dimensional matrices (mts). For the moment, I hold it in different objects: 1. a four-dimensional array for the spatial related analyses 2. a two-dimensional mts timeserie, which was

Dear All, I have a collections of spatial data. I have to analyze pairs of these point patterns to test their spatial interaction. I was moving towards the cross K Ripley's function. The problem, however, are the following: 1) What is the best way to get a single real value that represents the interaction "power"? 2) How to obtain a value that even allows me to rank the pairwise

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

Dear sirs, I'm using the Splancs package to compute standard errors of the estimates of a spatio-temporal k function. When I use as spatial and temporal distances too long vectors (respectively 60 and 80 entries) for a dataset of 1000 observations, R gives me the message Error: cannot allocate vector of size 180000 Kb Reached total allocation of 512 Mb. I ran the function memory.size()

Dear R-listers, I would like to carry out a very basic descriptive analysis of homicides rates in Italy, taking into account both the spatial dimension (103 provinces) and the temporal dimension (10 years), but no covariates. In practice, what I would like to do is to describe spatio-temporal variation of homicide rates, identifying those combinations of province-year where the homicide rate

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> library(SpatioTemporal) > library(plotrix) > library(maps) > palay.cov<-read.csv("C:/Users/BEDANA-PC/Desktop/STThesisWD/Thesis Data/palay.covar.csv") > palay.o<-read.table("C:/Users/BEDANA-PC/Desktop/STThesisWD/Thesis Data/palay.obs.txt") > palay.obs<-as.matrix(palay.o) > palay.stc<-read.table("C:/Users/BEDANA-PC/Desktop/STThesisWD/Thesis

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-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,

Greetings I'm using R 2.8 with recent (last month) versions of the packages I need to use at present. I'm interested in examining hierarchical spatio-temporal patterns in a data set. The data consist of 94 points (X, Y, UTM coordinates) at which catch rates for a fish were recorded and there are also estimates of prey available for these fish at the same locations.

The NOAA National Centers for Coastal Ocean Science is hiring a Computational Ecologist, a statistical/computational ecologist with experience fitting advanced spatial models to marine wildlife survey data (e.g., seabirds and marine mammal transects, fisheries trawl surveys) in R and other statistical languages. This is a full-time, long-term stable contract position. We are looking for an

Dear Simon, Thank you for your quick reply! I used to perform the GAMsetup in the following manner: GAMsetup sintax: x.summer: vector used for construct the spline knots<-14 N<-length(x.summer) x<-array(x.summer,dim=c(1,N)) G<-list(m=1,n=N,nsdf=0,df=knots+1,dim=1,s.type=0,by=0,by.exists=FALSE,p.order=0,x=x,n.knots=knots,fit.method="mgcv") H<-GAMsetup(G) with the

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,

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]]