similar to: Multiple Scaffolds

Hi, I''m using "Agile Web Dev. w/Rails", which is great but has a minimum on grouping controllers into modules. I''ve successfully generated a module scaffold, so I have: app/controllers/admin_controller.rb app/controllers/admin/things_controller.rb (And the rest of the scaffold output, which seems normal.) However, browsing to http://localhost:3000/admin/things/

Greetings, I''m fairly noob with rails and making my first DB driven site with it. I''m using the scaffold generator to develop the admin side of my site (admin_controller) I have three sections that I want to have the administrator edit, and I want to call these from the admin controller that has a layout with navigation to these three sections. When using the scaffold

Is there some way to have these two sets of URLs use totally different controllers and templates? categories/list categories/show/1 admin/categories/list admin/categories/edit/1 admin/categories/destroy/1 admin/categories/update/1 Besides, of course, using different controller names ;). The first URL is publicly accessible, while the second contains admin functions. Also, with the second,

Hi everyone, I have recently experienced a strange behavior (strange from my knowledge) in rails. In my controllers ''new'' action, I am creating a few instance variables in the following manner : @controllerModel = ControllerModel.new @model1 = Model1.all @model2 = Model2.all in my ''new'' view, I am using the @controllerModel to create the form for new and I

Hi, I have a large matrix (SNPs) that I want to cycle over with logistic regression with interaction terms. I have made a loop but I am struggling to identify to the formula the name of the column in a way which is meaningful to the formula. It errors becasue it is not evaluated proporly. (below is a pilot with only 7 to 33 columns, my actual has 200,000 columns) My attempts: for (i in 7:33)

Dear R users, i'm using a custom function to fit ancova models to a dataset. The data are divided into 12 groups, with one dependent variable and one covariate. When plotting the data, i'd like to add separate regression lines for each group (so, 12 lines, each with their respective individual slopes). My 'model1' uses the group*covariate interaction term, and so the coefficients

I was working on a project involving a linear model, and wanted to extract the standard error of a predictor. I am able to do so, but not in the way I would expect. I would have expected that if a created a model such as Model1 <- lm(y~x,z,d), the object Model1 would contain that information even though it does not print it out when I simply type Model1. I would also have (wrongly)

The "tsdiag" function in the TSA package overrides the "tsdiag" function in the "stats" package. There are a few annoying bugs in the TSA's version of the function so I would like to use the "stats" function but still have access to other TSA functions. I have tried using stats::tsdiag( ) but as long as the TSA package is attached the function from

this is getting frustrating... i installed file_column without a hitch for the first time to just play around with. using the exact same steps as before, i try to use it with one of my actual applications, and i get "permission denied" errors. i figure there might be some conflict with my application so just for kicks i do the exact same thing i did the first time to test

Hello, I would like to write a loop to 1) run 100 linear regressions, and 2) compile the slopes of all regression into one vector. Sample input data are: y1<-rnorm(100, mean=0.01, sd=0.001) y2<-rnorm(100, mean=0.1, sd=0.01) x<-(c(10,400)) #I have gotten this far with the loop for (i in 1:100) { #create the linear model for each data set model1<-lm(c(y1[i],y2[i])~x)

I would like to know how R computes the probability of an event in a logistic model (P(y=1)) from the score s, linear combination of x and beta. I noticed that there are differences (small, less than e-16) between the fitting values automatically computed in the glm procedure by R, and the values "manually" computed by me applying the reverse formula p=e^s/(1+e^s); moreover I noticed

Hello, I am trying to use the multi_search method, but I keep getting type error on nil objects, I send it [Model1,Model2] and it seems as though the class names keep getting clobbered and turn to nil, somewhere along the multi_index area. I tried to trace what was going on, but I got nothing, also, this only happens when there are actually hits(thank god, most of the time). Perhaps some insight?

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

Dear r-helpers, Spencer Graves and Manual Morales proposed the following methods to simulate p-values in lme4: ************preliminary************ require(lme4) require(MASS) summary(glm(y ~ lbase*trt + lage + V4, family = poisson, data = epil), cor = FALSE) epil2 <- epil[epil$period == 1, ] epil2["period"] <- rep(0, 59); epil2["y"] <- epil2["base"]

Dear R users, I would like to extract df and Mean Sq values. I tried several things (e.g., str(model1), names(model1)) but I can't find a way to extract these values. I also tried to search using RSiteSearch. Any help will be appreciated. Thanks Taka, model1<-aov(dv~iv.1*iv.2*iv.3) summary(model1) Df Sum Sq Mean Sq iv.1 1 3.200 3.200

Dear List: I am having difficulties with the fitted values at different levels of a multilevel model. My data set is a series of student test scores over time with a total of 7,280 observations, 1,720 students nested witin 60 schools. The data set is not balanced. The model was fit using eg.model.1<-lme(math~year, random=~year|schoolid/childid, data=single). When I call the random

If I have a model line = lm(y~x1) and I want to use a for loop to change the number of explanatory variables, how would I do this? So for example I want to store the model objects in a list. model1 = lm(y~x1) model2 = lm(y~x1+x2) model3 = lm(y~x1+x2+x3) model4 = lm(y~x1+x2+x3+x4) model5 = lm(y~x1+x2+x3+x4+x5)... model10. model_function = function(x){ for(i in 1:x) { } If x =1, then the list

Greetings, Apologies for such a simple question, but I have been trying to figure this out for a few days now (I'm quite new to R), have read manuals, list posts, etc., and not finding precisely what I need. I am accustomed to working in Stata, but I am currently working through the multilevel package right now. In Stata, I would include the statement "if model1 == 1" at the end

I''m following the Depot tutorial in the Rails book, and have just hit a wall. As instructed by the tutorial, I added the following code to the Product model: protected def validate errors.add(:price, "should be positive") unless price > 0.0 end When I attempt to add a new product, I''m getting an error: undefined method `>'' for nil:NilClass

Dear List, I'm having problem with an exercise from The R book (M.J. Crawley) on page 567. Here is the entire code upto the point where I get an error. data(UCBAdmissions) x <- aperm(UCBAdmissions, c(2, 1, 3)) names(dimnames(x)) <- c("Sex", "Admit?", "Department") ftable(x) fourfoldplot(x, margin = 2) dept<-gl(6,4) sex<-gl(2,1,24)