similar to: retrieving gbif data

NESCent Hackathon on Comparative Methods in R Call for Participation and Input The R statistical analysis package has emerged as a popular platform for implementation of powerful comparative phylogenetic methods to understand the evolution of organismal traits. The National Evolutionary Synthesis Center (NESCent) is organizing a hackathon focused on the integration of

Dear R community, I am trying to do a split-plot analysis as follows. I have a data set (?morf?) with plant data from 6 ?blocks? at different latitudes, each divided in 3 plots. The full-plot ?treatment? is ?soil type? and has three levels. Within each plot I have two levels of radiation, coded as ?SUN? and ?SHADE?. I have data for several response traits for 30 plants within each subplot,

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"

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"),

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

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]

random selection of cells in raster based on distance from xy locations Hi, I am trying to sample a raster for random cells that occur within a specific distance of point locations. I have successfully found multiple ways of doing this but have memory issues with very large datasets. To overcome this problem I am working with lists. I am now stuck on how to randomlly sample the correct elements

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

Hello, I've seen this upgrade error posted before: https://lists.samba.org/archive/samba/2013-January/171022.html but either there is a different issue or I'm misreading the post. Basically when I run the classicupgrade (samba3 to 4) on a test machine, I get the following (the full debug output will be at the end of my post): ....... key added: key=CurrentVersion,key=Windows

Dear all, I am currently running an ENFA in R using Adehabitat pkg to assess species distribution and I am really stuck and need some help to finalize my project. I run the ENFA in both original location data and pseudo-absence points (the latter randomly generated using dismo pkg), and now I would like to assess the performance of the ENFA, however, I am not sure about how to tackle this. I

Hi, I am looking for a way to save the result of a function, e.g the lm()-function to a file and reload it afterwards again. I'd like to do that in order to minimize the used memory when running the function in a loop. The actual function I want to store is the evaluate() from the dismo package. I tried it with save() and load() but I am not sure if that is the way I should do it as I

Hi R user, Could you please give me some hints on how I can convert text in table format in R? I was doing model assessment using dismo package for example: bg <- randomPoints(current, 500) pvtest <- data.frame(extract(current, occtest)) avtest <- data.frame(extract(current, bg)) e2 = evaluate(model, p=pvtest, a=avtest) > e2 class : ModelEvaluation n presences : 10 n

Hi R User, I was trying to find a final model in the following example by using the Boosted regression trees (GBM). The program gives the fitted values but I wanted to calculate the fitted value by hand to understand in depth. Would you give moe some hints on what is the final model for this example? Thanks KG ------- The following script I used #----------------------- library(dismo)

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

Hola de nuevo. Se me olvidaba la principal razón para utilizar gbm.step del paquete dismo. Como sabéis, los boosted si sobreajustan (a diferencia de los random forest o cualquier otro bootstrap) pero gbm.step hace validación cruzada para determinar el nº óptimo de árboles y evitarlo. Es fundamental. La opción que me queda, Carlos, es hacerlo con gbm, pero muchas veces, y usar el

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 R-helpers, I can not invoke maxent() in Mac OSX. Could you give me any directions on that? Thank you in advance. Here is my info: # (1) the error > me <- maxent(predictors, occtrain, factors='biome') me <- maxent(predictors, occtrain, factors='biome') Error in .jcall(mxe, "S", "fit", c("autorun", "-e", afn, "-o",

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]]

Samba 2.2.8a-1, RH8. ... So, I had to reinstall. Fortunately I had a back-up copy. I've installed everything and then went to back-up and brought back all the stuff from /etc/samba and /var/cache/samba and all /etc/cups and /etc/printcap*. Aparently samba is working corectly: All user/machine accounts are in place winbind OK... It's just that although I've restored the /home/printers