similar to: randomForest - what is a 'good' pseudo r-squared?

Hi I am trying to explore the use of random forests for regression to identify the important environmental/microclimate variables involved in predicting the abundance of a species in different habitats, there are approx 40 variable and between 200 and 500 data points depending on the dataset. I have successfully used the randomForest package to conduct the analysis and looked at the %IncMSE

Hi I am using R version 2.7.2. on a windows XP OS and have a question concerning an analysis of covariance with count data I am trying to do, I will give details of a scaled down version of the analysis (as I have more covariates and need to take account of over-dispersion etc etc) but as I am sure it is only a simple problem but I just can't see how to fix it. I have a data set with count

Hi all I am hoping this is just a minor problem, I am trying to implement a best subsets regression procedure on some ecological datasets using the regsubsets function in the leaps package. The dataset contains 43 predictor variables plus the response (logcount) all in a dataframe called environment. I am implementing it as follows: library(leaps)

Hi I have some experimental data where I have counts of the number of insects collected to different trap types rotated through 5 different location (variable -location), 4 different chemical attractants [A, B, C, D] were applied to the traps (variable - semio) and all were trialled at two different CO2 release rates [1, 2] (variable CO2) I also have a selection of continuous variables

Hello, Sometimes I have to create and use Navision Databases on samba shares - this works with samba 2.0.x but does not with samba 2.2.x (tried 2.2.3a and 2.2.4). The following tests were done with a acl enabeled samba and an acl aware kernel/filesystem, but I also have done these tests with acl not compiled into samba on an host without acl in the kernel - same result, does not work, same

Hi all I seem to have fallen at the first hurdle with my analysis, I have a set of binary disease outbreak data linked to a large number of landscape metrics variables and environmental variables which I would like to as predictor variables in a Least Angle Logistic Regression using the glars.fit.s function in the glars package (my data exhibits some multicollinearity hence the LARS) but when I

Hi I am trying to perform a bootstrap estimate of classification accuracy of a logistic regression using the 'Daim' package in r using the code at the bottom of this post, this all works great and I get the .632+ misclassification accuracy, specificity, sensitivity, AUC etc etc but what I would like is to access the list of AUC for each of the bootstrap samples as I need calculate the 95%

Hi everybody, I used randomForest to regress invertebrates abundances in least impaired river reaches from some environmental parameters. Then I used these models to predict invertebrates abundances in impaired reaches. Now I would like to model the deviation (observation - prediction) with a set of chemical parameters to see if the deviations from predictions could be explained with water

Hi guys, I'm very new to R and have been teaching myself over the past few months - it's a great tool and I'm hoping to use it to analyse my PhD data.As I'm a bit of a newb, I'd really appreciate any feedback and/or guidance with regards to the following questions that relate to generalized linearmixed modelling (or, at least, I think they do!)(if there is a 'better',

I'm having the most curious error while using the sem package. For the model I'm working with, I keep getting the following error: Error in J[cbind(1:n, observed)] <- 1 : subscript out of bounds I''ve used debug=TRUE with sem, and there don't appear to be any problems with model - there are no latent variables in this model. The variables in the covariance matrix

Hello All, I have a list of dataframes, and I need to subset it by keeping only those dataframes in the list that meet a certain criterion. Specifically, I need to generate a second list which only includes those dataframes whose number of rows is > 1. Could someone suggest how to do this? I have come close to what I need with loops and such, but there must be a less clumsy way... Many

Hello All, I have a data.frame with this structure: m <- matrix(sample(c(rep('yes', 10, replace = TRUE), rep('no', 10, replace = TRUE), NA), 500, replace = TRUE), nrow = 100, ncol = 5) colnames(m) <- colnames(m, do.NULL = FALSE, prefix = "col") m <- as.data.frame(m) I need to generate a Venn diagram from this data.frame, displaying the various intersections of

Dear List, I have a large (1600*1600) matrix generated with symnum, that I am using to eyeball the structure of a dataset. I have abbreviated the column names with the abbr.colnames option. One way to get an even more compact view of the matrix would be to display the column names rotated by 90 degrees. Any pointers on how to do this would be most useful. Any other tips for displaying the

Lara: I see you sent this email to the R helpdesk a really long time ago, but I was just wondering if you ever got an answer to this question. I was just thinking that I would build my own cross validation function, but if you figured out a way to do this automatically, could you let me know? Thanks, Eric Weine.

Dear All, Could someone please suggest how to find the Kronecker sum of two 2x2 matrices, i.e. given two matrices: -A A a -a and -B B b -b I need: -A-B A B 0 a -a-B 0 B b 0 -A-b A 0 b a -a-b Many thanks, Lara [[alternative HTML version deleted]]

Dear List, I am using function recode, from package car, within sapply, as follows: L3 <- LETTERS[1:3] (d <- data.frame(cbind(x = 1, y = 1:10), fac1 = sample(L3, 10, replace=TRUE), fac2 = sample(L3, 10, replace=TRUE), fac3 = sample(L3, 10, replace=TRUE))) str(d) d[, c("fac1", "fac2")] <- sapply(d[, c("fac1", "fac2")], recode, "c('A',

I'm looking over good-code a post-doc in my lab wrote and trying to learn how it works. I came across the following: rel.abundance <- as.matrix(read.delim("rel.abundance.csv",row.names=1,as.is =TRUE)) rel.abundance <- log2(rel.abundance-min(rel.abundance)+1) I'm not sure what the second line is doing. I ran each line in R and couldn't see a noticeable difference in

Hi everyone, I'm having problems with plotting my data. I have a set of positions with different attributes and I'm wondering if I can plot it, as x,y plot, with gradient colours according to a 3rd factor. Is it possible to show gradient segments between postions and not one-coloured segment between each one? I've been trying plotrix color.scale.lines with no luck. I'm very

Hola a todos Me gustaría saber si me pueden ayudar con lo siguiente. Realicé un Boxplot usando ggplot2 para visualizar el comportamiento de dos variables. Visualmente no se notan las diferencias porque la gráfica de la derecha (parásitos en el abdomen) llega hasta 20 en el eje y. ¿Cómo puedo hacer para que las dos gráficas muestren la misma escala en el eje Y, es decir, que las dos lleguen a 60?

Hi all, I am fairly new to R and I am trying to run mvpart and create a MRT using explanatory variables and covariables. I've been following the procedures in Numerical Ecoogy with R. The command (no covariables) which works fine - ABUNDTMRT <- mvpart(abundance ~ .,factors,margin=0.08,cp=0,xv="1se",xval=nrow(abundance),xvmult=100,which=4) where abundance is 4th root