similar to: Array as time series?

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

Dear [R] people, I am looking for a method to test if there are any changes (jump points) in a time series data set or not. If there are, I would like to identify the jump points. All the data is available from the beginning so an offline method could be used. The current data set that I have could be seen as a time series with five almost equally sized segments that stands out to have different

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 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

Let me start with an example: par(mfrow=c(2,3)) for (i in 1:5){ x = rnorm(100) y = .5*x + rnorm(100, 0, sqrt(1-.5^2)) plot(x,y) } Note that there's five plots and six spaces for those plots via mfrow, leaving one row empty. Is there a way to have the bottom two plots centered? I think it looks weird to have them left-justified. Thanks in advance for the help! -- Dustin Fife PhD

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

> 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

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

I have used Sweave a lot the latest year, but never really used any long function calls. If I have code which look like this ------------------------------------------------------------- gof <- benthic.flux(ID="Gulf of Finland", meas.conc=conc, bw.conc=bw.conc, time=times,

I'd greatly appreciate your help in making a bar graph with multiple variables plotted on it. All the help sites I've seen so far only plot 1 variable on the y-axis Data set: I have 6 sites, each measured 5 times over the past year. During each sampling time, I counted the occurrences of different benthic components (coral, dead coral, sand, etc.) over 5 transects in each site site

I have a data assimilation problem that might be amenable to the use of GAMS, but I am not sure how feasible it is to implement. I was told the R mailing list was a great resource. My observations are spatiotemporal salinity in the San Francisco Bay at a number of instruments over a few days. The thing that I want to fit is the initial condition for a salt transport model at the beginning of this

Sorry, I know I should read a little 1st about this, but I am actually just helping somebody really quick and need help too. I want to grep all of the names of the .txt files mentioned on this html web page: http://www.epa.gov/emap/remap/html/three/data/index.html Thanks ahead of time. -- View this message in context:

I have the following timeseries "tab" ===================================== > str(tab) mts [1:23, 1:2] 79.5 89.1 84.9 75.7 72.8 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr [1:2] "Ipex...I" "Omel...E" - attr(*, "tsp")= num [1:3] 2006 2008 12 - attr(*, "class")= chr [1:2] "mts" "ts" > tab

Dear members, I am performing multivariate analysis on marine benthic populations using R. At first glance I found ca and VEGANO packages to be the suitable for the task, but neither has incorporated Detrended Canonical Correspondence Analysis (DCCA), which is just the method I want to apply on my data. I've looked for alternative packages containing the method, but my suspicion is that

I am trying to create a high low close style chart but I keep getting the following error statement; "x is not a open/high/low/close time series". I've used the function is.ts and R responds TRUE but the ohlcPlot function gives the above error statement. I'm actually planning to plot some odds ratios with their confidence intervals and the hi-low-close chart should do the

Estimados, Les tengo una pequeña consulta. Estoy trabajando con ASReml en Rstudio, me encuentro corriendo un modelo (CHL) para obtener el ANOVA de la interacción de los factores gen x env CHL<- asreml(fixed= MS~geno:env, random = ~rep, data = index) (interacción) Sin embargo, cuando ejecuto el modelo, R indica que siguiente mensaje: Current workspace: 128.000000Mb Warning message: Abnormal

I am getting the following: *** Weave Errors *** Error in driver$runcode(drobj, chunk, chunkopts) : Error in eval(expr, envir, enclos) : couldn't find function "pacf.mts" *** Source Errors *** Error in eval(expr, envir, enclos) : couldn't find function "pacf.mts" make[1]: *** [checkVignettes] Error 1 I don't really understand the new namespace mechanism,