similar to: variable transformation for lm

Hello, I'm currently trying to model the movement of a slope (v.obs) with a regression model. The data can be found following the given links: either http://www.sendspace.com/file/dnugwc or http://rapidshare.com/files/420569660/sel.day.txt I want to use the Box-Cox transformation to normalize the response as well as the predictor variables. The scatterplot looks like this: library(zoo)

Hi, I just started with writing functions in R and so some questions popped up. I provide some values as argument to my function such as: function(a,b,c){} Now i want that the function first checks if the arguments are valid for the function. E.g argument "a" has to be a number in the range 0-1. How can that easily done? So far I have: a <- as.numeric(a) if(0 <= a &&

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

Just to inform: I posted that before in R-sig-ecology but as it might be interesting also for other useRs, I post it also to the general r-user list: Hello Alexandre, thank you very much. I also found another way to extract summarizing information from lm results over e.g. 1000 repeated model runs: results2 <- t(as.data.frame(results)) summary(results2) Although some questions popped up in

Hi, I have a dataframe and want to remove columns from it that are populated with a similar value (for the total column) (the variation of that column is 0). Is there an easier way than to calculate the statistics and then remove them by hand? A <- runif(100) B <- rep(1,100) C <- rep(2.42,100) D <- runif(100) df <- data.frame(A,B,C,D) # if want to conditionally remove column B and

Hello, just to follow up a question from last week. Here what I've done so far (here an example): library(MCMCpack) Y=c(15,14,23,18,19,9,19,13) X1=c(0.2,0.6,0.45,0.27,0.6,0.14,0.1,0.52) X2a=c(17,22,21,18,19,25,8,19) X2b=c(22,22,29,34,19,26,17,22) X2 <- function()runif(length(X2a), X2a, X2b) model1 <- MCMCregress(Y~X1+X2()) summary(model1) but I am not sure if my X2-function is

Hi, I have a 1-column dataframe with rownames and I want to sort it based on the single column. The typical procedure that is recommended in diverse posts is to use order in the index. But that "destroys" my dataframe structure. Probabaly it is a very simple solution. Here is a short reproducable example: x <- c(1,3,51,2,34,44,12,33,2,8) df <- data.frame(x) rownames(df) <-

Hi, I'd like to know if it is possible to use wildcards * for indexing... E.g. I have a vector of strings. Now I'd like to select all elements which start with A_*? I'd also need to combine that with logical operators: "Select all elements of a vector that start with A (A*) OR that start with B (B*)" Probably that is quite easy. I looked into grep() which I think might

Hello, assume we have following dataframe: group <-c(rep("A",5),rep("B",6),rep("C",4)) x <- c(runif(5,1,5),runif(6,1,10),runif(4,2,15)) df <- data.frame(group,x) Now I want to select all cases (rows) for those groups which have more or equal 5 cases (so I want to select all cases of group A and B). How can I use the indexing for such questions? df[??]...

Hi, I would like to plot some extra text in my plot. This should be a two line text including a special character (sigma). I tried so far a to use expression in combination with paste and "\n"... but I can't get the line break... Here what I've done so far: plot(1,type="n", xaxt='n', yaxt='n', ann=FALSE) text(1,1,labels=expression(paste(sigma,"\n

Dear All, Is there a way to find bandwidths for Normal, and Triangular Kernels using Sheather Jones plug-in method. If not, is there a way we could convert the bandwidth obtained by the default( I assume that the default is standard normal) in hcj(x,...) to other kernels. I appreciate your help. Thanks Durai --------------------------------- [[alternative HTML version

Hi, I used to use reshape and moved to reshape2 (R 2.15.1). Now I tried some of my older scripts and was surprised that my cast function wasn't working like before. What I did/want to do: 1) Melt a dataframe based on a vector specifying column names as measure.vars. Thats working so far: dfm <- melt(df, measure.vars=n, variable_name = "species", na.rm = FALSE) 2) Recast the

Hi, I want to split a dataframe based on a grouping variable (in one column). The resulting new dataframes should be stored in a new variable. I tried to split the dataframe using split() and to store it using a FOR loop, but thats not working so far: df <- data.frame(A=c("A1","A1","A2","A2"),B=seq(1:4)) Fsplit <- function(x,y){ ls <-

Hello, probably it is quite easy but I can get it: I have mulitple numeric vectors and a function using all of them to calculate a new value: L <- c(200,400,600) AR <- c(1.5) SO <- c(1,3,5) T <- c(30,365) fun <- function(L,AR,SO,T){ exp(L*AR+sqrt(SO)*log(T)) } How can I get an array or dataframe where all possible combinations of the factors are listed and the new value is

Hello, I'd like to perform a regression using MCMCregress (MCMCpack). One variable therefore should be a function rather than a variable: I want to use X as an input and X should be defined as a random number between to values. Therefore I want to use the function runif like: X <-(1, Xa, Xb) but it seems that runif doesn't allow to use vectors. So I think I've to calculate the new

Hello, I've some questions concerning log-transformations and plotting of the regression lines. So far as I know is it a problem to log-transform values smaller than 1 (0-1). In my statistics lecture I was told to do a log(x+1) transformation in such cases. So I provide here a small example to explain my questions: # Some example data for testing a1

Hello, I've a question concerning the display of interval data. A sample dataset where X is an interval between Xa and Xb which should be displayed: Y=c(15,14,23,18,19,9,19,13) Xa=c(17,22,21,18,19,25,8,19) Xb=c(22,22,29,34,19,26,17,22) X = (Xa+Xb)/2 It's easily possible to plot the mean of the interval like: plot(X,Y) afterwards I can create lines for the interval with:

Hi, I have got a dataset with the variables Y,X1,X2,X3. Some of these variables contain NAs. Therefore incomplete datasets aren't recognized when I am doing a regression like: model <- lm(Y~X1+X2+X3) so the resulting vector of resid(model) is obviousely shorter then the original variables. How can I combine the residuals-vector with the original dataset (Y,Xi,...). I recognize that the

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, it is easiest to explain what I want to do by an example: lets assume there are two factors/variables: A <- c(1,2,3) B <- c(1,3,3) Now I would like to generate a list of strings that should look like ("A1_B1","A1_B2","A2_B1","A2_B2"). So actually the string contains all possible combinations of A and B (separated by _). This should be also