-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 [Sorry to those who don't like it for top-posting]
Thierry, I'm curious whether this addresses your problem (although we don't have a hard timetable for the next release [it has to avoid conflicts with the 3.2.0 release in 2.5 weeks at the very least], so this might be problematic if your package needs to depend on it). I'm still curious whether there are any ideas/opinions from other readers. Has anyone else struggled with this? Is there a canonical solution? Ben Bolker On 15-03-24 07:55 PM, Ben Bolker wrote: > On 15-03-23 12:55 PM, Thierry Onkelinx wrote: >> Dear Ben, > >> Last week I was struggling with incorporating lme4 into a >> package. I traced the problem and made a reproducible example ( >> https://github.com/ThierryO/testlme4). It looks very simular to >> the problem you describe. > >> The 'tests' directory contains the reproducible examples. >> confint() of a model as returned by a function fails. It even >> fails when I try to calculate the confint() inside the same >> function as the glmer() call (see the fit_model_ci function). > >> Best regards, > >> Thierry > > > Ugh. I can get this to work if I also try searching up the call > stack, as follows (within update.merMod). This feels like "code > smell" to me though -- i.e., if I have to hack this hard I must be > doing something wrong/misunderstanding how the problem *should* be > done. > > > if (evaluate) { ff <- environment(formula(object)) pf <- > parent.frame() ## save parent frame in case we need it sf <- > sys.frames()[[1]] tryCatch(eval(call, env=ff), error=function(e) { > tryCatch(eval(call, env=sf), error=function(e) { eval(call, pf) }) > }) } else call > > Here is an adapted even-more-minimal version of your code, which > seems to work with the version of update.merMod I just pushed to > github, but fails for glm(): > > > ## > https://github.com/ThierryO/testlme4/blob/master/R/fit_model_ci.R > fit_model_ci <- function(formula, dataset, mfun=glmer){ model <- > mfun( formula = formula, data = dataset, family = "poisson" ) ci <- > confint(model) return(list(model = model, confint = ci)) } > > library("lme4") set.seed(101) dd <- > data.frame(f=factor(rep(1:10,each=100)), y=rpois(2,1000)) > fit_model_ci(y~(1|f),dataset=dd) > fit_model_ci(y~(1|f),dataset=dd,mfun=glm) > > > > > >> ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / >> Research Institute for Nature and Forest team Biometrie & >> Kwaliteitszorg / team Biometrics & Quality Assurance >> Kliniekstraat 25 1070 Anderlecht Belgium > >> To call in the statistician after the experiment is done may be >> no more than asking him to perform a post-mortem examination: he >> may be able to say what the experiment died of. ~ Sir Ronald >> Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner >> The combination of some data and an aching desire for an answer >> does not ensure that a reasonable answer can be extracted from a >> given body of data. ~ John Tukey > >> 2015-03-22 17:45 GMT+01:00 Ben Bolker <bbol...@gmail.com>: > >> WARNING: this is long. Sorry I couldn't find a way to compress >> it. > >> Is there a reasonable way to design an update method so that it's >> robust to a variety of reasonable use cases of generating calls >> or data inside or outside a function? Is it even possible? >> Should I just tell users "don't do that"? > >> * `update.default()` uses `eval(call, parent.frame())`; this >> fails when the call depends on objects that were defined in a >> different environment (e.g., when the data are generated and the >> model initially fitted within a function scope) > >> * an alternative is to store the original environment in which >> the fitting is done in the environment of the formula and use >> `eval(call, env=environment(formula(object)))`; this fails if the >> user tries to update the model originally fitted outside a >> function with data modified within a function ... > >> * I think I've got a hack that works below, which first tries in >> the environment of the formula and falls back to the parent >> frame if that fails, but I wonder if I'm missing something much >> simpler .. > >> Thoughts? My understanding of environments and frames is still, >> after all these years, not what it should be ... > >> I've thought of some other workarounds, none entirely >> satisfactory: > >> * force evaluation of all elements in the original call * >> printing components of the call can get ugly (can save the >> original call before evaluating) * large objects in the call get >> duplicated * don't use `eval(call)` for updates; instead try to >> store everything internally * this works OK but has the same >> drawback of potentially storing large extra copies * we could try >> to use the model frame (which is stored already), but there are >> issues with this (the basis of a whole separate rant) because the >> model frame stores something in between predictor variables and >> input variables. For example > >> d <- data.frame(y=1:10,x=runif(10)) >> names(model.frame(lm(y~log(x),data=d))) ## "y" "log(x)" > >> So if we wanted to do something like update to "y ~ sqrt(x)", it >> wouldn't work ... > >> ================== update.envformula <- function(object,...) { >> extras <- match.call(expand.dots = FALSE)$... call <- >> getCall(object) for (i in names(extras)) { existing <- >> !is.na(match(names(extras), names(call))) for (a in >> names(extras)[existing]) call[[a]] <- extras[[a]] if >> (any(!existing)) { call <- c(as.list(call), extras[!existing]) >> call <- as.call(call) } } eval(call, >> env=environment(formula(object))) ## enclos=parent.frame() >> doesn't help } > >> update.both <- function(object,...) { extras <- >> match.call(expand.dots = FALSE)$... call <- getCall(object) for >> (i in names(extras)) { existing <- !is.na(match(names(extras), >> names(call))) for (a in names(extras)[existing]) call[[a]] <- >> extras[[a]] if (any(!existing)) { call <- c(as.list(call), >> extras[!existing]) call <- as.call(call) } } pf <- >> parent.frame() ## save parent frame in case we need it >> tryCatch(eval(call, env=environment(formula(object))), >> error=function(e) { eval(call, pf) }) } > >> ### TEST CASES > >> set.seed(101) d <- data.frame(x=1:10,y=rnorm(10)) m1 <- >> lm(y~x,data=d) > >> ##' define data within function, return fitted model f1 <- >> function() { d2 <- d lm(y~x,data=d2) return(lm(y~x,data=d2)) } >> ##' define (and modify) data within function, try to update ##' >> model fitted elsewhere f2 <- function(m) { d2 <- d; d2[1] <- >> d2[1]+0 ## force copy update.default(m,data=d2) } ##' define (and >> modify) data within function, try to update ##' model fitted >> elsewhere (use envformula) f3 <- function(m) { d2 <- d; d2[1] <- >> d2[1]+0 ## force copy update.envformula(m,data=d2) } > >> ##' hack: first try the formula, then the parent frame ##' if >> that doesn't work for any reason f4 <- function(m) { d2 <- d; >> d2[1] <- d2[1]+0 ## force copy update.both(m,data=d2) } > >> ## Case 1: fit within function m2 <- f1() >> try(update.default(m2)) ## default: object 'd2' not found m3A <- >> update.envformula(m2) ## envformula: works m3B <- >> update.both(m2) ## works > >> ## Case 2: update within function m4A <- f2(m1) ## default: >> works try(f3(m1)) ## envformula: object 'd2' not found m4B <- >> f4(m1) ## works > >>> >>> ______________________________________________ >>> R-devel@r-project.org mailing list >>> https://stat.ethz.ch/mailman/listinfo/r-devel >>> > > > -----BEGIN PGP SIGNATURE----- Version: GnuPG v1.4.11 (GNU/Linux) iQEcBAEBAgAGBQJVFc1CAAoJEOCV5YRblxUHF+MH/3Y9uFZFolhx5b5jWSyXwQgp i9oawx4K6il0qiAiDiO5D7NSSdc0u9jlgj8NjH0G2O9u3ctpvcYNVwa7cP9288Xz xRyInnnh2FIpT6W0XyzJDivw5EX3IkyYuv6eDNqVyGcYXkvzJMA+vwMMWdGWEZbL jKtDc0trG+9yJnwIi6DW6IQWPovrDaNxEinS+V7+DmYACQvJ4P2kg2u/ZsxAx89q mcA1pS5usJjkOiQwBVUvV7l2UKNhHPFNwbBK1QdHgpP7PTdB52EQr+IyERhpf56s 8tYyNbSSPWoG9vt6/1pKyUK4iNRBtGgxtuozAv5OUjF8VGWGwUXBLo5G2yrBbs4= =o1PJ -----END PGP SIGNATURE----- ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
