similar to: confint() in stats4 package

Dear R developers, I noticed a bug in the stats4 package, specifically in the confint method applied to ?mle? objects. In particular, when some ?fixed? parameters define the log likelihood, these parameters are stored within the mle object but they are not used by the ?confint" method, which retrieves their value from the global environment (whenever they still exist). Sample code: >

Following up on this -- on my system, I have 69 packages installed that appear to provide something like a confint() method: h <- help.search("confint", agrep = FALSE) p <- sort(unique(h$matches$Package)) length(p) ## [1] 69 p [1] "bamlss" "bbmle" "binom" "brglm2" [5] "broom"

Hi, There is something I don't get with object of class "mle" returned by a function I wrote. More precisely it's about the behaviour of method "confint" and "profile" applied to these object. I've written a short function (see below) whose arguments are: 1) A univariate sample (arising from a gamma, log-normal or whatever). 2) A character string

Hi there, When I do bootstrap on a maximum likelihood estimation, I try the following code, however, I get error: Error in minuslogl(alpha = 0, beta = 0) : object "x" not found It seems that mle() only get data from workspace, other than the boot.fun(). My question is how to pass the data to mle() in my case. I really appreciated to any suggestions. Best wishes, Jinsong

? Tue, 21 May 2024 08:00:11 +0000 Dario Strbenac via R-devel <r-devel at r-project.org> ?????: > Would a less resource-intensive value, such as 1, be a safer default > CPU value for confint? Which confint() method do you have in mind? There is at least four of them by default in R, and many additional classes could make use of stats:::confint.default by implementing vcov(). >

Here's a patch that should make predict.glm(..., type="response") retain the names. The change passes make check on our Opteron running SLES9. One simple test is: names(predict(glm(y ~ x, family=binomial, data=data.frame(y=c(1, 0, 1, 0), x=c(1, 1, 0, 0))), newdata=data.frame(x=c(0, 0.5, 1)), type="response")) which gives [1]

Hi the list, I am experiencing several issues with profile.mle (and consequently with confint.mle) (stat4 version 2.9.2), and I have to spend a lot of time to find workarounds to what looks like interface bugs. I would be glad to get feedback from experienced users to know if I am really asking too much or if there is room for improvement. * Problem #1 with fixed parameters. I can't

A few hours ago, I was making a small point on the R-SIG-robust mailing list on the point that ifelse() was not too efficient in a situation where pmax() could easily be used instead. However, this has reminded me of some timing experiments that I did 13 years ago with S-plus -- where I found that pmin() / pmax() were really relatively slow for the most common case where they are used with only

[posted to R-devel, no discussion: resubmitting it as a bug, just so it gets logged appropriately] Sorry to report further difficulties with nls and profiling and constraints ... the problem this time (which I didn't check for in my last round of testing) is that the nls profiler doesn't seem to respect constraints that have been set when using the port algorithm. See test code

Dear R user, I have written a function which returns max,min and variation of a power (see below) Power is a given matrix(1,n) I call the function >Variation<-VAR(p,(n-deltat)) Now the problem is when I want plot(Results[1],Results[2]). Not possible! I become the following error (in english it means: Error in as.double.default(x) :Object cannot be transformed in double) >

The documentation says, "pmax and pmin take several vectors as arguments and return a single vector giving the parallel maxima (or minima) of the vectors." I discovered that, if you use a matrix or array instead of a vector, pmax returns a matrix or array, respectively. This makes pmax and pmin much more useful, and should not be left to people to discover on their own! For example:

Yes, functions like c, min and max are special cases, as they are primitives. For ordinary functions, you just need to promote them with "..." as the signature: setGeneric("pmax", signature="...") setMethod("pmax", "Class", function(..., na.rm=FALSE) { }) One caveat is that all arguments passed via "..." must derive from the class

I stumbled on the following: > library(stats4) > example(mle) > confint.default(fit2) Error in UseMethod("vcov") : no applicable method for "vcov" In addition: Warning message: In object$coefficients : $ operator not defined for this S4 class, returning NULL > vcov(fit2) lymax lxhalf lymax 0.02857612 -0.04870231 lxhalf -0.04870231 0.11457338

Hi everyone, I am wondering what¹s stopping the LLVM optimizer (opt -O3) from eliminating the apparently useless « icmp sgt » instruction in the following piece of LLVM IR. > ; ModuleID = 'lambda-opt.bc' > target datalayout = "e-m:o-i64:64-f80:128-n8:16:32:64-S128" > target triple = "x86_64-apple-macosx10.10.0" > > ; Function

I can't get confint.glm to work from within a function. Consider the following (using R 1.9.1, Windows 2000): # FIRST: SOMETHING THAT WORKS FROM A COMMAND PROMPT DF <- data.frame(y=.1, N=100) (fit <- glm(y~1, family=binomial, data=DF, weights=DF[,"N"])) Call: glm(formula = y ~ 1, family = binomial, data = DF, weights = DF[, "N"]) Coefficients:

>>>>> steven pav >>>>> on Thu, 19 Jul 2018 21:51:07 -0700 writes: > It seems that confint.default returns an empty data.frame > for objects of class mlm. For example: > It seems that confint.default returns an empty data.frame for objects of > class mlm. Not quite: Note that 'mlm' objects are also 'lm' objects, and so it is

Hello, I'm trying to override pmin and pmax for my own matrix. These two functions have ... as an argument. I tried to override them as follows: setMethod("pmax", class_name, function(x, ..., na.rm) { ... }) I use this way to override primitive functions such as min/max and it works fine. But it doesn't work for pmin and pmax. I guess because they are regular functions? How

Dear R users, The nnet package includes the multinom method for the confint function. The R Help file (?confint) for the generic function in the stats package and the help files for the glm and nls methods in the MASS package indicate that one can use the "parm" argument as "a specification of which parameters are to be given confidence intervals, either a vector of numbers or

Dear R users, I'm trying to write a function which returns minimum,maximum,mean of a vector(power) I've done the following : VAR<-function(power,length){ for(i in tml:length)){ tvar[i]<-i pmean[i]<-mean(power[i:i+deltat]) pmin[i]<-min(power[i:i+deltat]) pmax[i]<-max(power[i:i+deltat]) varmax[i]<-100*(pmax[i]-pmean[i])/pmean[i]

Sorry to report further difficulties with nls and profiling and constraints ... the problem this time (which I didn't check for in my last round of testing) is that the nls profiler doesn't seem to respect constraints that have been set when using the port algorithm. See test code below ... If I can I will try to hack the code, but I will probably start by redefining my function with