similar to: problem with using transace

Hello, I''m trying to implement something like the following scenario. I''ve got "Alloys" (blends of metals), "Metals" and "Percentages" I want to implement this using a join model, not using a has_and_belongs_to_many relationship. (If i''m wrong about that, let me know). Basically, i have the following tables: Metals id name Alloys

Hello people In my rails 3.0.9 app I''m trying to add nested attributes dynamically, but I don''t want to use "nested form gem" So I found this example https://github.com/alloy/complex-form-examples/blob/a234fde4419836f277d7e340657f1d8418911d68/app/helpers/projects_helper.rb but this code doesn''t work module ProjectsHelper def

I found the old ace function (from acepack) valuable a couple of years ago in helping to find a transformation of the response to approximate additivity in smooth functions of the predictors. ace used alternating conditional expectations, but I'm not overly fixated on algorithms as long as it works pretty well. Is there another package that has that sort of functionality? I haven't been

Hi! I''m running rails 2.3.8, confirmed by the prompt (rails -v) I''m doing a project and on other occasions I have needed install nested forms. I followed the steps (http://weblog.rubyonrails.org/2009/1/26/nested-model-forms) This steps: $ git clone git://github.com/alloy/rails.git $ cd rails $ git checkout origin/normalized_nested_attributes $ cd ../.. $ ruby

Hi folks, I'm trying to estimate bias-corrected percentile (BCP) confidence intervals on a vector from a simple for loop used for resampling. I am attempting to follow steps in Manly, B. 1998. Randomization, bootstrap and monte carlo methods in biology. 2nd edition., p. 48. PDF of the approach/steps should be available here: https://wyocoopunit.box.com/s/9vm4vgmbx5h7um809bvg6u7wr392v6i9 If

Is there any way to put an argument into an object name. For example, say I have 5 objects, model1, model2, model3, model4 and model5. I would like to make a vector of the r.squares from each model by code such as this: rsq <- summary(model1)$r.squared for(i in 2:5){ rsq <- c(rsq, summary(model%i%)$r.squared) } So I assign the first value to rsq then cycle through models 2 through

I?ve been using Frank Harrell?s rms package to do bootstrap model validation. Is it the case that the optimum penalization may still give a model which is substantially overfitted? I calculated corrected R^2, optimism in R^2, and corrected slope for various penalties for a simple example: x1 <- rnorm(45) x2 <- rnorm(45) x3 <- rnorm(45) y <- x1 + 2*x2 + rnorm(45,0,3) ols0 <- ols(y

R-Listers: I am doing a quasi-maximum likelihood estimation and I get a "subscript out of bound" error message, Typically I would think this means that a subscript used in the function is literally out of bounds however I don't think this is the case. All I change in the code is a constant, that is hard-wired in (not data dependent and not parameter dependent), furthermore,

Christoph -- There was just a thread on this earlier this week. You can search in the archives for the title: "refitting lm() with same x, different y". (Actually, it doesn't turn up in the R site search yet, at least for me. But if you just go to the archive of recent messages, available through CRAN, you can search on refitting and find it. The original post was from William

Does this give correct results for special floats (0, infs)? We tried to improve (for single floats) x86 rcp in llvmpipe with newton-raphson, but unfortunately not being able to give correct results for these two cases (without even more additional code) meant it got all disabled in the end (you can still see that code in the driver) since the problems are at least as bad as those due to bad

I think I am doing something wrong when I try to bootstrap R square obtained from lm. My code is included below. No matter how many times I run the simulation, I always get exactly the same result, the bias and std.error are always zero. I would think that these values should be non-zero. I would appreciate any suggestions as to what I am doing wrong, or perhaps what I fail to understand. R 2.1.0

Dear UseR, I get an error when I run "R CMD check" on my .tar.gz file package, and I don't understand why since I don't obtain any error with "R CMD check" on the package directory. Do you have any idea ? $ sudo ./R-2.11.0/bin/R CMD check eqtl_1.1.tar.gz and $ sudo ./R-2.11.0/bin/R CMD --check-subdirs=no eqtl_1.1.tar.gz return an Error * checking for working

Hello everybody, I'm a new user of R and I'm working right now with the ACE function from the acepack library. I Have a question: Is there a way to predict new responses using ACE? What I mean is doing something similar to the following code that uses PPR (Projection Pursuit Regression): library(MASS) x <- runif(20, 0, 1) xnew <- runif(2000, 0, 1) y <- sin(x) a <- ppr(x, y,

Hi, I'm a new user of R and I'm trying to make a linear model from this kind of dataset x [1] 16.87 19.93 25.85 20.94 17.06 19.49 19.93 25.45 27.74 20.15 25.81 21.06 17.17 20.03 25.50 27.79 20.44 16.88 19.93 25.79 z<-x-10 y [1] 0.80 1.27 2.22 1.32 0.90 1.18 1.84 2.41 2.97 1.25 2.07 1.41 1.14 1.66 2.59 3.51 1.53 0.81 1.26 2.30 plot(x,y) I want to be able to force the line of

I have a vaiable named NAM having value : 1,2,3,4,5,6,7,8,9. I want to make an indicator variable that will take value 1 if NAM=7 or NAM=8 or NAM=9. How can I do that? I usually do: Var001<- ifelse(NAM==7,1,0) for the simplest case. [[alternative HTML version deleted]]

My understanding is that R will not make copies of lists if there is only one reference to the object. However, I've encountered a case where R does make copies, even though (I think) there should be only one reference to the object. I hope that someone could shed some light on why this is happening. I'll start with a simple example. Below, x is a list with one element, and changing that

Hello, I've a problem with a self written routine taking a lot of memory (>1.2Gb). Maybe you can suggest some enhancements, I'm pretty sure that my implementation is not optimal ... I'm creating many linear models and store coefficients, anova p-values ... all I need in different lists which are then finally returned in a list (list of lists). The input is a matrix with 84 rows

Hi All? I was looking at a posting from June-17. I managed to solve it. However, when I changed the example in the posting, my solution will work only once at a time which was mentioned by Jim Lemon on his response to the original posting. This means that my solution will have to be repeated as many times as the maximum number of spaces on each gap; something that may not work well for large

Dear all,   i would like to count the number of times where I have combined occurrences of the categories of 2 variables.   For instance, in the dataframe below, i would like to know how many times each author (au1, au2, au3 represent the first, second, third author) is associated with each of the category of the variable 'nam'. The position of the author does not matter.   nam <-

Dear all, I want to improve my adj - R sq. I 've chequed some established models and they introduce two times the same variable, one transformed, and the other not. It also improves my adj - R sq. But, isn't this bad for the collinearity? Do I interpret coefficients as usual? Estimate Std. Error t value Pr(>|t|) (Intercept) 1.73140 7.22477 0.240