As far as I can tell from the docs, strt & frm1 should be the simplest model, 'y1~1', since we’re doing stepAIC in the forward direction.
I found that using 'y1~.' for frm2 doesn't always work, hence the explicit enumeration of the xvars into a full formula. I had forgotten that you don't need the +1 term. With real data, if you start from the most complex model and go backwards, stepAIC just over-fits and gives up [for same reason I set the steps parameter]. Cheers, SGO -----Original Message----- From: Bert Gunter [mailto:bgunter.4...@gmail.com] Sent: 22 August 2017 18:51 To: Stephen O'hagan <soha...@manchester.ac.uk> Cc: r-help@r-project.org Subject: Re: [R] boot.stepAIC fails with computed formula SImplify your call to lm using the "." argument instead of manipulating formulas. > strt <- lm(y1 ~ ., data = dat) and you do not need to explicitly specify the "1+" on the rhs for lm, so > frm2<-as.formula(paste(trg," ~ ", paste(xvars,collapse = "+"))) works fine, too. Anyway, doing this gives (but see end of output)" bst <- boot.stepAIC(strt,data = dat,B=50,alpha=0.05,direction='forward',steps=limit, scope=list(lower=frm1,upper=frm2)) > bst Summary of Bootstrapping the 'stepAIC()' procedure for Call: lm(formula = y1 ~ ., data = dat) Bootstrap samples: 50 Direction: forward Penalty: 2 * df Covariates selected (%) x1 100 x2 100 x3 100 x4 100 x5 100 x6 100 x7 100 x8 100 Coefficients Sign + (%) - (%) x3 100 0 x6 100 0 x8 100 0 x1 90 10 x2 86 14 x7 62 38 x4 44 56 x5 0 100 Stat Significance (%) x3 100 x6 100 x8 100 x5 34 x2 20 x1 16 x4 10 x7 4 The stepAIC() for the original data-set gave Call: lm(formula = y1 ~ x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8, data = dat) Coefficients: (Intercept) x1 x2 x3 x4 x5 42.008824 0.012304 0.010925 0.976469 -0.005183 -0.021041 x6 x7 x8 2.000649 0.004461 3.007071 Stepwise Model Path Analysis of Deviance Table Initial Model: y1 ~ x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8 Final Model: y1 ~ x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8 Step Df Deviance Resid. Df Resid. Dev AIC 1 191 16.14592 -485.33 HOWEVER, I do not know why your failed calls failed. In view of the above, it appears to be a bug in the formula interface, so if you do not get a satisfactory answer here (i.e. I am wrong about this), you should contact the maintainer. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Tue, Aug 22, 2017 at 10:08 AM, Steve O'Hagan <soha...@manchester.ac.uk> wrote: > The error is "the model fit failed in 50 bootstrap samples > Error: non-character argument" > > Cheers, > SOH. > > > On 22/08/2017 17:52, Bert Gunter wrote: >> >> Failed? What was the error message? >> >> Cheers, >> >> Bert >> >> >> Bert Gunter >> >> "The trouble with having an open mind is that people keep coming >> along and sticking things into it." >> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) >> >> >> On Tue, Aug 22, 2017 at 8:17 AM, Stephen O'hagan >> <soha...@manchester.ac.uk> wrote: >>> >>> I'm trying to use boot.stepAIC for feature selection; I need to be >>> able to specify the name of the dependent variable programmatically, >>> but this appear to fail: >>> >>> In R-Studio with MS R Open 3.4: >>> >>> library(bootStepAIC) >>> >>> #Fake data >>> n<-200 >>> >>> x1 <- runif(n, -3, 3) >>> x2 <- runif(n, -3, 3) >>> x3 <- runif(n, -3, 3) >>> x4 <- runif(n, -3, 3) >>> x5 <- runif(n, -3, 3) >>> x6 <- runif(n, -3, 3) >>> x7 <- runif(n, -3, 3) >>> x8 <- runif(n, -3, 3) >>> y1 <- 42+x3 + 2*x6 + 3*x8 + runif(n, -0.5, 0.5) >>> >>> dat <- data.frame(x1,x2,x3,x4,x5,x6,x7,x8,y1) >>> #the real data won't have these names... >>> >>> cn <- names(dat) >>> trg <- "y1" >>> xvars <- cn[cn!=trg] >>> >>> frm1<-as.formula(paste(trg,"~1")) >>> frm2<-as.formula(paste(trg,"~ 1 + ",paste(xvars,collapse = "+"))) >>> >>> strt=lm(y1~1,dat) # boot.stepAIC Works fine >>> >>> #strt=do.call("lm",list(frm1,data=dat)) ## boot.stepAIC FAILS ## >>> >>> #strt=lm(frm1,dat) ## boot.stepAIC FAILS ## >>> >>> limit<-5 >>> >>> >>> stp=stepAIC(strt,direction='forward',steps=limit, >>> scope=list(lower=frm1,upper=frm2)) >>> >>> bst <- >>> boot.stepAIC(strt,dat,B=50,alpha=0.05,direction='forward',steps=limit, >>> scope=list(lower=frm1,upper=frm2)) >>> >>> b1 <- bst$Covariates >>> ball <- data.frame(b1) >>> names(ball)=unlist(trg) >>> >>> Any ideas? >>> >>> Cheers, >>> SOH >>> >>> >>> [[alternative HTML version deleted]] >>> >>> ______________________________________________ >>> 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 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.
