search for: mymodels

Hi all, Initially I thought this was a bug in the built-in mocking framework(and it still may be), but I better hash it out on the mailing list before I file/reopen the ticket: http://rspec.lighthouseapp.com/projects/5645/tickets/478-mocks-on-constants#ticket-478-6 I thought my example illustrated my problem, but obviously I was passing the wrong arguments to the mock. I revised my example to

I have a list object, in which I have stored n lme4-models. For example: library(lme4); myModels <- list(); myModels[1] <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy) myModels[2] <- lmer(Reaction ~ Days + (1|Subject) + (0+Days|Subject), sleepstudy) Now I would like to perform an anova over all models in the list. However, the anova function requires that every model is inserte...

Hello! I am using package "VAR". I've fitted my model: mymodel<-VAR(mydata,myp,type="const") I can extract the Log Liklihood for THE WHOLE MODEL: logLik(mymodel) How could I calculate (other than manually) the corresponding Akaike Information Criterion (AIC)? I tried AIC - but it does not take mymodel: AIC(mymodel) # numeric(0) Thank you! -- Dimitri Liakhovitski

I have dose response data analyzed with the package 'drc'. 'summary(mymodel)' prints my kinetic parameters. I want that text in an ASCII text file. I want to get exactly what I would get if I copied and pasted from the terminal window. I've read the documentation on data export to text files here:

Hi everyone, Can someone please help me in these questions?: 1)if I use crossvalidation with svm, do I have to use this equation to calculate RMSE?: mymodel <- svm(myformula,data=mydata,cross=10) sqrt(mean(mymodel$MSE)) But if I don’t use crossvalidation, I have to use the following to calculate RMSE: mymodel <- svm(myformula,data=mydata) mytest

Hello again, I guess this is more of a Ruby question, but here goes anyways... I want to intercept all calls to non existent class methods and then call an existing class method with the non existent name. In code... class MyModel < ActiveRecord::Base def MyModel.method_missing(symbol, *args) MyModel.func(symbol.id2name) end def MyModel.func(func_called) puts "You

This should be very easy, but alas, I'm very new to R. My end goal is to calculate p-values from arima(). Let's say I just ran this: > MyModel <- arima(y[1:58], order=c(1,0,0), xreg=MyData[1:58,7:14], > method="ML") > MyModel And I see: arima(x = y[1:58], order = c(1, 0, 0), xreg = MyData[1:58, 7:14], method = "ML") Coefficients: ar1

Dear list, I made a logistic regression model (MyModel) using lrm and penalization by pentrace for data of 104 patients, which consists of 5 explanatory variables and one binary outcome (poor/good). Then, I found bootcov and robcov function in rms package for calculation of confidence range of coefficients and odds ratio by bootstrap covariance matrix and Huber-White sandwich method,

?sink On May 18, 2018 9:47:25 AM PDT, Ed Siefker <ebs15242 at gmail.com> wrote: >I have dose response data analyzed with the package 'drc'. >'summary(mymodel)' prints my kinetic parameters. I want >that text in an ASCII text file. I want to get exactly what I >would get if I copied and pasted from the terminal window. > >I've read the documentation on

Buenos días: Tengo un determinado código en R que en una máquina funciona correctamente, pero en otra devuelve un error del tipo "Error en as.formula(mymodel): Objeto ''mymodel'' no encontrado''" En mi código: mymodel <- "y ~ x1[, 1] + x2[, 1]" res <- lm (as.formula(mymodel)) ¿Qué puede estar motivando ese error?. La máquina en la que falla

I''m getting confused. If I have a view (.rhtml), I can use a field helper like: <%= text_field :mymodel, :attribute %> This uses the value from @mymodel.attribute Now, if I am rendering a template normally (i.e. not partial), I would expect @mymodel to be a model object defined as an instance variable in the controller. However, if I am rendering a partial template, I

Can anyone show me how to refer to an object name that is passed to a function, from within the function? For example: MyModel <- 1 test <- function(x) { if(x == 1) {cat("x is a valid object.\n")} } test(x) What I would like this to do is pass MyModel to function test, and if it passes a test, be able to print "MyModel is a valid object." Thanks. -- View this

In my environment.rb I say the following: MyModel.disable_ferret puts MyModel.ferret_enabled? The console works as expected: script/console false >> MyModel.ferret_enabled? => false I can then edit an instance, ferret remains disabled and the changes are not immediately indexed. However, when I start mongrel Ferret is initially disabled, but then somehow becomes enabled again

Dear users, I'll appreciate your help with this (hopefully) simple problem. I have a model object which was fitted to inputs X1, X2, X3. Now, I'd like to use this object to make predictions on a new data set where only X1 and X2 are available (just use the estimated coefficients for these variables in making predictions and ignoring the coefficient on X3). Here's my attempt but, of

Can anybody share some examples of their Money implementation ? I''m trying to setup a Model to use this library, but can''t seem to wrap my head around how it is exactly supposed to work. My Model (Foo) looks like: =============== composed_of :commission, :class_name => "Money", :mapping => [ %w(commission_cents cents), %w(commission_currency currency) ] Yet, in

Please excuse yet another newbie question... I''m getting this error: MissingSourceFile in <controller not set>#<action not set> c:/program files/ruby/lib/ruby/gems/1.8/gems/actionpack-1.8.1/lib/action_controller/dependencies.rb:75:in `require_dependencies'': Missing model MyModel.rb From these lines of code: class MyModelController < ApplicationController

Hi, everyone. I am using a fair amount of closures in my code. Problem i am experiencing is i cannot figure out how to mtrace functions defined within a function. There must be some way to name such function for mtrace to see it and let me step into it. For example, say i have code mymodel<-function(){ data<-numeric(0) build<-function(){ data<<-1 } m<-list()

Hello, I'd like to create a model with a factor-type response variable. This is an example: > mydata <- data.frame(factor_var = as.factor(c(rep('one', 100), rep('two', 100), rep('three', 100))), real_var = c(rnorm(150), rnorm(150) + 5)) > summary(mydata) factor_var real_var one :100 Min. :-2.742877 three:100 1st Qu.:-0.009493 two

Hi everyone I have a question about how to save a regression model in R and how to retrieve it for making predictions in a new session. To be more specific, I fitted a multilevel logistic regression model using the lmer from the "lme4" package. I then successfully make predictions using fitted(mymodel). Since data are complex (three levels, nested, numerous categorical and

Is there a way to undo this? because mymodel wasn''t a model, but only a class... :)