Eric,
you are right! If I run the code on a different instance, it works.
There must be something in my old R environment that messed this up.
Thank you very much for checking this out.
Best,
Valerio
On Wed, Aug 19, 2020 at 11:36 AM Eric Berger <ericjber...@gmail.com> wrote:
>
> Hi Valerio,
> I did a copy-paste on your reproducible example and I had no problem with
> chol(nls.out$hessian).
> In addition to summary() you can look at str() to display the structure of
> any R object.
>
> > str(nls.out)
>
> List of 9
> $ par :List of 3
> ..$ a: num 8.99
> ..$ b: num -1.01
> ..$ c: num 6.02
> $ hessian : num [1:3, 1:3] 10.3 43.2 19.9 43.2 382.2 ...
> ..- attr(*, "dimnames")=List of 2
> .. ..$ : chr [1:3] "a" "b" "c"
> .. ..$ : chr [1:3] "a" "b" "c"
> $ fvec : num [1:100] 0.0232 -0.105 -0.1332 0.0388 0.1482 ...
> $ info : int 1
> $ message : chr "Relative error in the sum of squares is at most `ftol'."
> $ diag :List of 3
> ..$ a: num 9.98
> ..$ b: num 88.6
> ..$ c: num 10
> $ niter : int 8
> $ rsstrace: num [1:9] 1966.2 327.2 104.8 53.9 33.2 ...
> $ deviance: num 1.06
> - attr(*, "class")= chr "nls.lm"
>
> Also
> > nls.out$hessian
> a b c
> a 10.26361 43.17086 19.89616
> b 43.17086 382.17773 166.43747
> c 19.89616 166.43747 100.00000
>
> HTH,
> Eric
>
>
>
> On Wed, Aug 19, 2020 at 12:17 PM Valerio Leone Sciabolazza
> <sciabola...@gmail.com> wrote:
>>
>> Dear R users,
>> I want to modify how the degrees of freedom are calculated from the
>> summary function of the package minpack.lm
>>
>> My first thought was to replicate how minpack.lm:::summary.nls.lm
>> works, and modify the line of the code that is relevant for my task.
>> However, for some reason I am not able to use the code contained in
>> this function to perform this operation.
>>
>> Here is a reproducible example.
>>
>> First, I run a NLLS regression using minpack.lm::nls.lm
>>
>> # From example 1 of the help page of ?minpack.lm::nls.lm
>> library(minpack.lm)
>> x <- seq(0,5,length=100)
>> getPred <- function(parS, xx) parS$a * exp(xx * parS$b) + parS$c
>> pp <- list(a=9,b=-1, c=6)
>> simDNoisy <- getPred(pp,x) + rnorm(length(x),sd=.1)
>> residFun <- function(p, observed, xx) observed - getPred(p,xx)
>> parStart <- list(a=3,b=-.001, c=1)
>> nls.out <- nls.lm(par=parStart, fn = residFun, observed = simDNoisy,
>> xx = x, control = nls.lm.control(nprint=1))
>> summary(nls.out)
>>
>> Now, by running minpack.lm:::summary.nls.lm in the console, I get the
>> following
>> > minpack.lm:::summary.nls.lm
>> function (object, ...)
>> {
>> param <- coef(object)
>> pnames <- names(param)
>> ibb <- chol(object$hessian)
>> ih <- chol2inv(ibb)
>> p <- length(param)
>> rdf <- length(object$fvec) - p
>> resvar <- deviance(object)/rdf
>> se <- sqrt(diag(ih) * resvar)
>> names(se) <- pnames
>> tval <- param/se
>> param <- cbind(param, se, tval, 2 * pt(abs(tval), rdf, lower.tail =
>> FALSE))
>> dimnames(param) <- list(pnames, c("Estimate", "Std. Error",
>> "t value", "Pr(>|t|)"))
>> ans <- list(residuals = object$fvec, sigma = sqrt(object$deviance/rdf),
>> df = c(p, rdf), cov.unscaled = ih, info = object$info,
>> niter = object$niter, stopmess = object$message, coefficients =
>> param)
>> class(ans) <- "summary.nls.lm"
>> ans
>> }
>>
>> Specifically, my task requires to modify the object p of this
>> function, say I want to set p <- 2.
>>
>> To this purpose, I replicate what the summary function does using my
>> object (nls.out), however an error is returned at line three:
>> > param <- coef(nls.out)
>> > pnames <- names(param)
>> > ibb <- chol(nls.out$hessian)
>> Error in array(x, c(length(x), 1L), if (!is.null(names(x))) list(names(x), :
>> 'data' must be of a vector type, was 'NULL'
>>
>> The reason of the error is that there is no nls.out$hessian in nls.out.
>>
>> I guess that I am missing something about how summary functions work,
>> and this is the reason why I cannot use the code from
>> minpack.lm:::summary.nls.lm outside the minpack.lm environment.
>>
>> Does anyone have any hints on how to proceed? Any other way of dealing
>> with this issue will be equally appreciated.
>>
>> Thank you,
>> Valerio
>>
>> ______________________________________________
>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
