similar to: MCMC regress, using runif()

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

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 UseRs, I've got 3 variables, the dependent variable Y as well as a max and a min value of the independent variable (Xa and Xb) where in some cases Xa=Xb (so actually a single value for X). First I'd like to perform a regression, but my problem is that my X is a range (acutally a censored independent variable Xa-Xb) rather then one single value. I know already some possible

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:

If I remove all the export and change all the ' in ", it does work on SCO 3.2v5.0.4 |--------+-----------------------------> | | Roumen Petrov | | | <Roumen.Petrov at skal| | | asoft.com> | | | | | | 21/12/00 13:10 | | | |

Q: What platform don't run this script: ---------------------------------------- #!/bin/sh export X0='x0' export X1a="$X0/1" export X1b='$X0/1' export X2a="$X1a/2" export X2b='$X1b/2' $SHELL <<EOF_2 $SHELL <<EOF_1 cat <<EOF #define a "$X2a/aa" #define b "$X2b/bb" EOF EOF_1 EOF_2

Hello, thank you very much for your previous answers about the C++ code. I am interested in the application of the Gibbs Sampler in the IRT models, so in the function MCMCirt1d and MCMCirtkd. I've found the C++ source codes, as you suggested, but I cannot find anything about the Gibbs Sampler. All the files are for the Metropolis algorithm. Maybe I am not able to read them very well, by the

Has anyone programmed condition indexes in R? I know that there is a function for variance inflation factors available in the car package; however, Belsley (1991) Conditioning Diagnostics (Wiley) notes that there are several weaknesses of VIFs: e.g. 1) High VIFs are sufficient but not necessary conditions for collinearity 2) VIFs don't diagnose the number of collinearities and 3) No one has

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

Hello Tyler, I want to bring to your attention the following document: "What happens if you omit the main effect in a regression model with an interaction?" (https://stats.idre.ucla.edu/stata/faq/what-happens-if-you-omit-the-main-effect-in-a-regression-model-with-an-interaction). This gives a useful review of the problem. Your example is Case 2: a continuous and a categorical regressor.

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 Tyler, Thank you for searching for, and finding, the basic description of the behavior of R in this matter. I think your example is in agreement with the book. But let me first note the following. You write: "F_j refers to a factor (variable) in a model and not a categorical factor". However: "a factor is a vector object used to specify a discrete classification"

Hi, I recently ran into an inconsistency in the way model.matrix.default handles factor encoding for higher level interactions with categorical variables when the full hierarchy of effects is not present. Depending on which lower level interactions are specified, the factor encoding changes for a higher level interaction. Consider the following minimal reproducible example: -------------- >

Hello Tyler, I rephrase my previous mail, as follows: In your example, T_i = X1:X2:X3. Let F_j = X3. (The numerical variables X1 and X2 are not encoded at all.) Then T_{i(j)} = X1:X2, which in the example is dropped from the model. Hence the X3 in T_i must be encoded by dummy variables, as indeed it is. Arie On Thu, Nov 2, 2017 at 4:11 PM, Tyler <tylermw at gmail.com> wrote: > Hi

I'm having some problems in installing some source packages under linux. As an example, MCMCpack. An error is raised when linking: > install.packages("MCMCpack") [...] * Installing *source* package 'MCMCpack' ... checking for C++ compiler default output file name... a.out checking whether the C++ compiler works... yes checking whether we are cross compiling... no checking

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 Tyler, You write that you understand what I am saying. However, I am now at loss about what exactly is the problem with the behavior of R. Here is a script which reproduces your experiments with three variables (excluding the full model): m=expand.grid(X1=c(1,-1),X2=c(1,-1),X3=c("A","B","C")) model.matrix(~(X1+X2+X3)^3-X1:X3,data=m)

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[??]...