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    Generating a multi-parameter space and sampling from it

    Hi all, I have a long list of combination of parameters which covary. I would like to sample from it but not exactly the same values. What I'd like to do is to create a multi-parameter space that accounts for the covariation and then sample from it the parameter values to create new...
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    Detecting duplicates for the first two col and selecting one according to a third col

    I have a database with only three columns but with many thousands of rows. The first and the second columns report numerical ID, and their combination indicate a link (e.g. A-B equal to B-A). Now, I need to delete all rows that are duplicates for the link, selecting the row with the highest...
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    Troubles in installing R on Mac OS X Mountain lion

    I all, In my previous mac, which had leopard installed, R was working perfectly. Now I just bought a new mac with Mountain Lion and I`m trying to install R. I`ve already installed all the required libraries, included Xcode 4.6, Xcode tools 4.6 and gfortran 4.2. However, when I run...
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    How to predict a model with multiple factors?

    Hi, My question is probably trivial but I cannot figure it out... I'm doing a glm with multiple continuous and categorical predictors. In R, the summary() gives the estimates of factors' levels as contrast to the intercept (right?). So, If I'm modelling, let's say, diet and sociality as...
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    Multiple regression with correlated predictors to check for explained variance

    Hi all, I have two predictive and one response variable and I'm trying to develop a model for predictions. Both predictors fit well (one slightly better than the other) and are well correlated each other (R2 = about 0.6-0.7). Anyway, when they are both used in multiple regression the fit...
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    How to deal with a categorical response and continuous and categorical predictors?

    Hi all, I have a large dataset of categorical and continuous variables, the observations are animal species. I want to test which variables are more influent in determining a categorical variables with 3 levels. So I have a categorical response variable (3 levels) and many possible predictors...
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    Using taxonomic levels as factors in random forests: does it make sense? Is it needed

    Hi all, I want to test the effect of a set of predictors (ecological and morphological factors) on a categorical response variable (an animal behaviour). As far as I've read, random forests do not make assumptions about data independence. Therefore, can I use species in my analysis...
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    Problems with Random Forests in R (empty classes and argument length 0)

    Hi, I'm dealing for the first time with random forests and I'm having some troubles that I can't figure out.. When I run the analysis on all my dataset (about 3000 rows) I don't get any error message. But when I perform the same analysis on a subset of my dataset (about 300 rows) I get an...
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    Factors in an nls model

    Hello, I have some nls model fitted with a four parameter logistic curve. model<-nls(V1 ~ SSfpl(V2, a, b, c, e)) I want to test the effect of a factor on this fit, something like: model<-nls(V1 ~ SSfpl(V2+factor, a, b, c, e)) or model<-nls(V1 ~ SSfpl(V2, a, b, c, e)+factor)...