similar to: Can not invoke maxent() of library(dismo) in Mac OSX

Dear R-helpers and Dr. Hijmans, I can not invoke maxent() in GNU Linux. Could you give me any directions on that? There is maxent.jar in version 3.3.3e in the right folder. ######################################## R: > jar <- paste(system.file(package="dismo"), "/java/maxent.jar", sep='') > jar [1] "/ebio/abt6/jmao/rpacks/dismo/java/maxent.jar"

I was going through this example of maxent use: http://cran.r-project.org/web/packages/maxent/maxent.pdf # LOAD LIBRARY library(maxent) # READ THE DATA, PREPARE THE CORPUS, and CREATE THE MATRIX data <- read.csv(system.file("data/NYTimes.csv.gz",package="maxent")) corpus <- Corpus(VectorSource(data$Title[1:150])) matrix <- DocumentTermMatrix(corpus) # TRAIN/PREDICT

Buenas días me gustaria saber cual es la libreria mas actual que contiene al algoritmo de maxima entropia que permite modelar nichos ecologicos; a su vez que libreria presenta mejor temática en la representacion de mapas. Saludos¡ [[alternative HTML version deleted]]

Dear all, when using .jinit() I get the message .jinit() : Cannot create Java virtual machine (-1). The details: I am using the Dismo package.Dismo has a function 'maxent' that communi-cates with this program(MaxEnt).MaxEnt is available as a stand-alone Java program. It is normal when I execute the command : "jar <- paste(system.file(package="dismo"),

Dear all, I get the error when I use maxent.jar: Error .jcall(mxe, "S", "fit", c("autorun", "-e", afn, "-o", dirout, : java.lang.NoSuchMethodError: density.Params.readFromArgs([Ljava/lang/String;)Ljava/lang/String; sessionInfo() result: R version 2.14.0 (2011-10-31)Platform: i386-pc-mingw32/i386 (32-bit)locale:[1]

savePngCentredAt <- function(address) { require(dismo) x <- geocode(address) range <- as.numeric(x[4:7]) + c(-0.01, 0.01, -0.01, 0.01) e <- extent(range) g <- gmap(e, type = "roadmap") require(digest) png(path.expand(paste('~/public_html/',digest(address, algo='sha1'),'.png',sep=''))) plot(g) dev.off() } The code above

Estimados erreros, Estoy intentando entender como calcula el paquete dismo ( https://cran.r-project.org/web/packages/dismo/index.html) un coeficiente de variación. Os pongo un ejemplo: tmin <- c(10,12,14,16,18,20,22,21,19,17,15,12) # temperatura mínima media mensual de un año tmax <- tmin + 5 # temperatura máxima media mensual de un año prec <- c(0,2,10,30,80,160,80,20,40,60,20,0)

Hola, en la misma definici?n de la funci?n: # P15. Precipitation Seasonality(Coefficient of Variation) # the "1 +" is to avoid strange CVs for areas where mean rainfaill is < 1) p[,15] <- apply(prec+1, 1, cv) Un saludo, Jorge On Martes, 19 de Junio de 2018 13:07:27 Marcelino de la Cruz Rot escribi?: > Hola Jaume: > > Si miras el c?digo de biovars() ver?s que la

Hi all ? I am a newbie to R and have had a terrible time trying to figure out how to set up an analysis.? I have installed and loaded the appropriate package (phyloclim), but I do not even know where to begin defining one of the arguments. The usage for the command I?m trying to perform is: niche.equivalency.test(spec, n, maxent, mx = 2000) where the argument? maxent???? is a list containing

Hello, I want to use a for loop for repeadely calculating a maxent model (package dismo, function maxent()) which creates an object of the class maxent (S4). I want to collect all the resulting object in a list. I tried to simplify my for loop to explain what I want. There are two problems/questions: 1) How can I create the new variables in the loop (using paste) and assign the objects 2) How

Hello. I am trying to use a FORTRAN subroutine from within R (Windows version). This fortran subroutine is compiled using the Open Watcom Fortran compiler and the compiled object file is called ritscale.obj. Following the explanation on pages 193-194 of "The New S language" I use the dyn.load command: > dyn.load("f:/maxent/ritscale.obj") Error in dyn.load(x,

Hi, I've got a dataset with 7 variables for 8 different species. I'd like to test the null hypothesis of no difference among species for these variables. MANOVA seems like the appropriate test, but since I'm unsure of how well the data fit the assumptions of equal variance/covariance and multivariate normality, I want to use a permutation test. I've been through CRAN looking at

Hello list, I seem to have a problem with the openNLP package, I'm actually stuck in the very beginning. Here's what I did: > install.packages("openNLP") > install.packages("openNLPmodels.de", repos = "http://datacube.wu.ac.at/", type = "source") > library(openNLPmodels.de) > library(openNLP) So I installed the main package as

Hello! First of all a question: When you make the encoder tables (ie: mode_e.h) do you use the mapping0_forward function? Because you made the encoder tables, and after this you did a minor correction in the final beta4 ... (this correction was: additional[0]=fabs(additional[0]*scale); in the mapping0_forward function) (I see this was a bug, and the modification was correct, but this correction

Hey, I am having troubles using the 'predict' function with in the Raster package. I am using pm<-predict(mm, predictors) where mm is the mahalanobis distance and the predictors are a stack of 6 raster layers containing environmental variables. When I try to run the prediction I get the following warning message: Warning message: In layerNames(x): the layerNames function is

Dear All I would really appreciate some help with a script which a colleague wrote for me (attached), but I am having problems running (and have not been able to contact my colleague). The script is designed to compare the area of suitable habitat in binary projections of a large number of species current and future distributions, and create an excel file detailing the total area suitable in the

Hi All, I'm trying to use the geoRglm package to run a poisson spatial glm on a dataset with several covariates. When I run without covariates I have no problems. control1.data.geo <- mcmc.control(S.scale=0.2, thin = 1) model1.data.geo <- list(cov.pars = c(1,1), beta=c(1), family="poisson") test1.model1 <- glsm.mcmc(data.geo, model=model1.data.geo,

Please keep your posts "on-list". You are much more likely to get a useful answer that way. There are many others on the list whose knowledge and insight are far greater than mine. I have therefore cc-ed the list in this reply. On 14/05/18 21:48, Soufianou Abou wrote: > Thank you for advice, Rolf Turner > > My question is as follows: > > I'd use maxent to

Dear All, The Decision and Policy Analysis (DAPA) program of the International Center for Tropical Agriculture (CIAT), a not-for-profit agriculture, biodiversity and ecosystems research center, supported by the Consultative Group of International Agricultural Research (CGIAR), with headquarters in Cali, Colombia is looking for a visiting researcher to work on various modeling projects, primarily

Dear All I would really appreciate some help with a script which a colleague wrote for me, but I am having problems running (and have not been able to contact my colleague). The script is designed to compare the area of suitable habitat in binary projections of a large number of species current and future distributions, and create an excel file detailing the total area suitable in the