similar to: constrained regression

Does this help on our backtest reporting? Regards, Gordon Morrison Global Head of Quantitative Research > * + 44 20 7653 7642 > Mob: + 44 7867 801951 > fax: + 44 20 7645 7442 > * mailto:gordon.morrison at commerzbankib.com > web: http://www.cbksec.com/research/quant > * Commerzbank Securities > 60 Gracechurch Street > London EC3V 0HR, U.K. >

Assignment to a list in a function does not behave as I would expect. The following function illustrates the point #---------------------------------------- temp _ function() { nf _ 2 ns _ 5 z _ vector("list",ns) x _ matrix(NA,nrow=ns,ncol=nf) for(j in 1:ns) { for(i in 1:nf) { x[,i] _ i+j*100 } z[[j]] _ x print(z[[j]]) } z }

Hi all, Using R a as a real-time application called by Php for a website, I would like to run one R process only, which would manage user connections. For the time each user who asks for an analysis causes a new R process to start, which is not suitable in prevision of many users. R needs about 30 seconds to run the script which makes the analysis. The problem is that this waiting time is n

I would like to figure out the equations for calculating "AIC" in both "step() function" and "AIC () function". They are different. Then I just type "step" in the R console, and found the "AIC" used in "step() function" is "extractAIC". I went to the R help, and found: "The criterion used is AIC = - 2*log L + k *

Dear R users: I am looking for the source code for the R function extractAIC. Type the function name doesn't help: > extractAIC function (fit, scale, k = 2, ...) UseMethod("extractAIC") <environment: namespace:stats> And when I search it in the R source code, the best I can find is in (R source root)/library/stats/R/add.R: extractAIC <- function(fit, scale, k = 2,

Full_Name: Dave Ramsey Version: 1.8.0 OS: win2000 Submission from: (NULL) (202.27.240.6) there is a bug in extractAIC.survreg in library MASS. A survreg model object has no component called "residuals". Hence n <- length(fit$residuals) returns 0 resulting in errors workaround: replace n <- length(fit$residuals) with n <- length(residuals(fit)) ### sorry: error

Dear R users, Would it be difficult to change the code of stepAIC (from the MASS library) to use AICc instead of AIC? It would be great to know of someone has tried this already. Best wishes Christoph.

By changing three lines in drop1 from access based on $ to access based on standard accessor methods (terms() and residuals()), it becomes *much* easier to extend drop1 to work with other model types. The use of $ rather than accessors in this context seems to be an oversight rather than a design decision, but maybe someone knows better ... In particular, if one makes these changes (which I am

Greetings everyone, I am new at R. My questions is rather basic. Looking R manuals looks like there should be a way to read MS excel files into R. Could somebody tell me which library should I use for that? Thanks in advance Victor H. Marín Laboratorio de Modelación Ecológica Depto. de Ciencias Ecológicas, Fac. de Ciencias, Universidad de Chile Casilla 653 Santiago, Chile

I am trying to perform a backwards stepwise variable selection with an mlogit model. The usual functions, step(), drop1(), and dropterm() do not work for mlogit models. Update() works but I am only able to use it manually, i.e. I have to type in each variable I wish to remove by hand on a separate line. My goal is to write some code that will systematically remove a certain set of variables

Although the 'spatial' documentation doesn't mention that extractAIC works, it does seem to give an output. I may have misunderstood, but shouldn't the following give at least the same d.f.? > library(spatial) > data(topo, package="MASS") > extractAIC(surf.ls(2, topo)) [1] 46.0000 437.5059 > extractAIC(lm(z ~ x+I(x^2)+y+I(y^2)+x:y, topo)) [1]

My question has two parts. The first is with regard to the frame or environment in which generic functions are defined in packages. It seems as though they are defined (i.e. exist as objects) in frame 1, even when defined in a package. The following is a short example: setClass("track",representation(x="numeric",y="numeric")) plotTrack <- function(x,y,...)

I would like test AICc as a criteria for model selection for a glm using stepAIC() from MASS package. Based on various information available in WEB, stepAIC() use extractAIC() to get the criteria used for model selection. I have created a new extractAIC() function (and extractAIC.glm() and extractAIC.lm() ones) that use a new parameter criteria that can be AIC, BIC or AICc. It works as

Has there been a recent change in the behavior of binary operators? In SparseM it was, until quite recently ok to do scalar multiplication but now, > A*4 Error in A * 4 : non-numeric argument to binary operator > 4*A Error in 4 * A : non-numeric argument to binary operator > A%*%A An object of class "matrix.csr" Slot "ra": [1] 1 1 1 Slot "ja": [1] 1 2 3

I am having problems getting the unz() function to work as a connection to start reading a file... z <- unz("c:/temp/stoxx.zip", "close_tmi_components.txt", "r") readLines(z,2) yields the following problems: > z <- unz("c:/temp/stoxx.zip", "close_tmi_components.txt", "r") Error in unz("c:/temp/stoxx.zip",

I am still experiencing problems with seq.POSIXt() missing off the last day of the series: > seq(as.POSIXct("2004-03-25"),as.POSIXct("2004-03-31"),by="DSTdays") [1] "2004-03-25 GMT Standard Time" "2004-03-26 GMT Standard Time" "2004-03-27 GMT Standard Time" [4] "2004-03-28 GMT Standard Time" "2004-03-29 GMT Daylight

Yes, lots of packages do use C/Fortran code ... it would be great if there were more packages that are "pure R" especially since the advent of S4 classes and namespaces. Is it worth suggesting that we create a designation "pure R" for packages that have no external source code and encourage more of these? Indeed, now the number of packages is so big could they be classified to

Hello, I am using a simple linear model and I would like to get an AIC value. I came across both AIC() and extractAIC() and I am not sure which is best to use. I assumed that I should use AIC for a glm and extractAIC() for lm, but if I run my model in glm the AIC value is the same if I use AIC() on an lm object. What might be going on? Did I interpret these functions incorrectly? Thanks,

Does anybody have some simple instructions to get me going using the GNU debugger GDB under windows with R? The R Extensions manual mentions briefly debugging under unix, but I've seen seen GDB mention in the Bloodshed Dev C++ IDE so it should be possible to use it with R? Regards, John [Using R-1.8.0 under Windows NT 4.0]

Hi Folks, I've got a question concerning the calculation of the Schwarz-Criterion (BIC) done by summary.regsubsets() of the leaps-package: Using regsubsets() to perform subset-selection I receive an regsubsets object that can be summarized by summary.regsubsets(). After this operation the resulting summary contains a vector of BIC-values representing models of size i=1,...,K. My problem