search for: gl1ce

Hi, I'm using gl1ce with family=binomial like so: >yy succ fail [1,] 76 23 [2,] 32 67 [3,] 56 43 ... [24,] 81 18 >xx c1219 c643 X1 0.04545455 0.64274145 X2 0.17723669 0.90392792 ... X24 0.80629054 0.12239320 >test.gl1ce <- gl1ce(yy ~ xx, family = binomi...

Hi, I tried several settings by using the "family=gaussian" in "gl1ce", but none of them works. For the case "glm" can work. Here is the error message I got: > glm(Petal.Width~Sepal.Length+Sepal.Width+Petal.Length ,data=iris,family=gaussian()) > gl1ce(Petal.Width~Sepal.Length+Sepal.Width+Petal.Length ,data=iris,family=gaussian()) Error in eval(e...

...0.1861905 -2.891821 4 1.938780097 0.7469251 1.2537781 -1.212992 5 -0.332370358 1.1943637 0.7114278 -1.830441 modF<-formula(F ~ V1 + V2 + V3) #no error message #general least squares model works fine glm.F <- glm(modF, data = F2, family = gaussian) #But there are unresolved errors with gl1ce gl1F<-gl1ce(modF, data=F2, family=gaussian) Error in family(family) : link "family" not available for gaussian family; available links are 'inverse', 'log', 'identity' > gl1F<-gl1ce(modF, data=F2, family=gaussian(link="identity"))...

All, Could anyone recommend a package that allows the user to constrain the coefficients from a multiple regression equation? I tried using the gl1ce function in lasso2, but couldn't get it to work. I created a contrived example to illustrate my starting point. data(cars) fmla <- formula(dist ~ speed) gl1c.E <- gl1ce(fmla, data = cars) gl1c.E gl1c.E <- gl1ce(fmla, data = cars, link=identity()) gl1c.E I started with the examp...

Full_Name: Grant Izmirlian Version: 2.2.0 OS: SuSe Linux version 9.2 Submission from: (NULL) (156.40.34.177) Sorry about the last submission, my bug-fix had an error in it because ifelse doesn't vectorize. I'll repost with the correct bug-fix. ------------------------------------------------------------------------------- The option exists to include all parameters, including the

Hi all, I want to know some details about the c routine “lasso” in the functions of “gl1ce()” . However, I have following troubles. First, I can not find the routine in the local directories of this function (or package). Second, if I found the routine, could I call it just like this way, say, fit <- .C("lasso", …,PACKAGE = "lasso2") in my own functions. My system...

Dear R-users, For the purpose of model selection I am looking for a way to exhaustively (and efficiently) search for best subsets of predictor variables for a logistic regression model. I am looking for something like leaps() but that works with glm. Any feedback highly appreciated. -- Harald von Waldow <hvwaldow at chem.ethz.ch> Safety and Environmental Technology Group Institute for

...524 1.227 9.392 < 2e-16 *** d 10.942 1.071 10.220 < 2e-16 *** e 3.688 1.124 3.282 0.001031 ** #so I wrote this below using the lasso2 package to determine the best shrinkage factor using the gcv cross-validation: for (i in seq(1,40,1)) { glmba=gl1ce(resp~a+b+c+d+e, data = w, family = binomial(),bound=i) ecco=round(gcv(glmba,type="Tibshirani",gen.inverse.diag =1e11),digits=3) print(ecco) } #and it gives me 21 with the lowest gcv. #then I determine the shrunken coefficients: >gl1ce( resp ~ a + b + c + d + e, data = w, family = bin...

...own to the following: > x <- matrix(rnorm(200), ncol=2) > var <- "fred" > apply(x, 2, var) Error in get(x, envir, mode, inherits) : variable "fred" of mode "function" was not found only that the "offending" apply() command happened inside the gl1ce() function of lasso2. I was under the impression that R can now distinguish between variables and functions with the same name and, indeed, the following works: > var <- 2 > apply(x, 2, var) [1] 1.053002 1.250875 Poking a bit around, I guess that the ability to distinguish between varia...

...ge glmulti does an exhaustive search of all models and gives a number of candidate models to choose from based on your choice of Information Criterion. This seems to be exactly what I am after, but I found nothing about it on this list which makes me think there is some reason no one is using it. gl1ce() in package lasso2 uses the least absolute shrinkage and selection operator (lasso) to do something. I found it at another thread: http://tolstoy.newcastle.edu.au/R/help/05/03/0121.html I did not understand the paper it was based on, and want to know if it even does what I am interested in before...