search for: forested

i hope you can help me. The game's site is http://withinadeepforest.ni2.se/index.php? here's the terminal output from the install (from install binary) and the run. the install: $ wine install_wadf_11.exe fixme:advapi:CheckTokenMembership ((nil) 0x7ff18088 0x7fc8fe1c) stub! fixme:sfc:SfcIsFileProtected ((nil), L"C:\\Program Files\\Within a Deep Forest\\unins000.exe") stub

Dear List, I am looking to calculate two things from my data frame and was after some advice. For the example below i want to know. 1. How many unique Orders/Families and Genera there are per eco-name 2. How many incidences are there for each Order/Family and Genus there are per eco-region I have 650 econame. I.e for Biak-Numfoor rain forests there are 2 orders, 2 families and two genera.

Hello, I'm trying to create a series of randomForest objects, basically in a loop like this: forests <- list(); for (level in 1:10) { # do some other things here # create a random forest forest <- randomForest( x = x.level, y = z.level, ntree = trees ); forests <- c(forests, forest); } But instead of creating a list of 10 forests, this creates a list

I am using metafor to create forest plots. This code gives me the expected plot (setting x axis tick marks): forest(forest$OR, ci.lb=forest$Low, ci.ub=forest$High, at=log(c(.05, .25, 1, 10)), slab=forest$SNP, atransf=exp) As does this (setting colors): forest(forest$OR, ci.lb=forest$Low, ci.ub=forest$High, col=c(1,2,3), slab=forest$SNP, atransf=exp) But if I try to set both 'at' and

Hi all, I've been trying to run a model using R2winBUGS, and recurrently I get the message: "Error in FUN(X[[3L]], ...) : invalid to change the storage mode of a factor" My model is the following: sink("GLMM_Poisson.txt") cat(" model{ mu~dnorm(0,0.01) beta1~dnorm(-1,1) for(j in 1:nsite){ alpha[j]~dnorm(mu.alpha,tau.alpha) } mu.alpha~dnorm(0,0.01)

Dear mailinglist members, I was wondering if there was a way to re-evaluate the instances of a tree (in the forest) again after I have manually changed a splitpoint (or split variable) of a decision node. Here's an illustration: library("randomForest") forest.rf <- randomForest(formula = Species ~ ., data = iris, do.trace = TRUE, ntree = 3, mtry = 2, norm.votes = FALSE) # I am

Dear Sir or Madam, I am trying to plot forest plot. I extracted odds ratio and their corresponding 95% confidence interval from papers, then I calculated the log(OR) and standard error using the following command OR<-metagen(logOR,selogOR,sm="OR") forest(OR,comb.fixed=TRUE,comb.random=TRUE,digits=2) However, it does not produce a forest plot. Can someone kindly help? Thank

Hello all, I have a *.csv file that looks like this (actual file is orders of magnitude larger): Site taxa no.ind forest LMA 1 forest LCY 1 forest SCO 1 meadow LMA 2 meadow LCY 1 meadow PNT

Hi! I am dealing with random forest using R. Is there a way to sample a fixed no.of rows from a dataset for use with different trees in random Forest. To be more clear, my data set contains 1500 rows, and I am growing 500 trees in Random Forest Is it possible to sample only 500 rows of data from the data set and use it for different trees in the forest. I mean each tree of the forest should use

Hi all, I am interested in performing a cluster analysis on ecological data from forests in Pennsylvania. I would like to develop definitions for forest types (red maple forests, upland oak forests, etc.(AH AR in attached table)) based on measured attributes in each forest type. To do this, I would like to 'draw clusters' around forest types based on information from various tree

OK - I've been doing some work on getting a forest plot or two together for a sub-group analaysis. Thats the crucial thing - because its a sub-group analysis rather than a meta-analsysis and all the forest (meta) and forestplot (rmeta) instructions assume you are doing a meta-analysis. I found rmeta didn't play nicely for me so I'm using the meta package with forest. Here's some

> > Hello All, > > I have been struggling with this for a long, long time. I came here > looking for answers. So, I have a VM running Debian Lenny. I install > the apt package samba, which installs 3.2.5. I work in a large > university with an extensive Active Directory environment, both forest > and domain running in Win2k native mode. There is a NetApp filer >

Guys, I used Random Forest with a couple of data sets I had to predict for binary response. In all the cases, the AUC of the training set is coming to be 1. Is this always the case with random forests? Can someone please clarify this? I have given a simple example, first using logistic regression and then using random forests to explain the problem. AUC of the random forest is coming out to be

now I am learining random forest and using random forest package, I can get the OOB error rates, and test set rate, now I want to get the training set error rate, how can I do? pgp.rf<-randomForest(x.tr,y.tr,x.ts,y.ts,ntree=1e3,keep.forest=FALSE,do.trace=1e2) using the code can get oob and test set error rate, if I replace x.ts and y.ts with x.tr and y.tr,respectively, is the error rate

Hi Kim and Others, Can anyone please help me on how can I edit default labels ( "Study 1", "Study 2",...) using forest() - same question as below. Which option I should try? It would be a great help. Thanks in advance, On Sun, Dec 13, 2009 at 7:14 PM, Kim Jung Hwa <kimhwamaillist@gmail.com>wrote: > Hi All, > > I'm using forest() from metafor package to

Dear Prof.Thank you for your kind response. I have only used: install.packages("tidyverse") install.packages("meta") install.packages("metafor") library(tidyverse) library(meta) library(metafor)and then,forest.meta(hidemeta, layout="RevMan5", xlab="Proportion", comb.r=T, comb.f=F, xlim = c(0,1), fontsize=10, digits=3)Unfortunately I am not

Hi, I need help with the randomForest prediction. i run the folowing code: > iris.rf <- randomForest(Species ~ ., data=iris, > importance=TRUE,keep.forest=TRUE, proximity=TRUE) > pr<-predict(iris.rf,iris,predict.all=T) > iris.rf$votes[53,] setosa versicolor virginica 0.0000000 0.8074866 0.1925134 > table(pr$individual[53,])/500 versicolor virginica 0.928

Dear Fahimeh It would help if you also told us what package you are using as there are several which perform forest plots. I assume it is meta. Your plot is cropped on three side as far as I can see. What parameters did you give to the call of the graphics device? What happens if you use a different graphics format like pdf? Then we may be able to see where the issue lies. Michael On

Dear R-experts, The forest.rma() function from the metafor package creates nice forest plots for presenting the results of a meta-analysis. These plots can be annotated for e.g. giving names to the columns. E.g. as in the documentation of the package: data(dat.bcg) ### meta-analysis of the log relative risks using a random-effects model res <- rma(ai=tpos, bi=tneg, ci=cpos, di=cneg,

Dear Prof.?My forest plot is not fit to windows in R software, I have 49 studies but forest plot only show from 9 to 42.? forest.meta(hidemeta, layout="RevMan5", xlab="Proportion", comb.r=T, comb.f=F, xlim = c(0,1), fontsize=10, digits=3) Whould you please help me to access full forest plot??Thank you Sincerely,Fahimeh Dr. Fahimeh AlizadehPost-Doctorate Fellow and