[RsR] 'ROptRegTS' load error

Johannes Graumann joh@nne@_gr@um@nn @end|ng |rom web@de
Mon Dec 1 17:10:43 CET 2008


Thank you very much for your help. Everything installs fine and your examples 
are running fine and very educational. I realized, however, that the showcased 
way of RobRex is not particularly suited for large amounts of data. I fed 
~9000 data points into "DiscreteMVDistribution" and it's calculating for hours 
... still waiting whether it will actually be able to finish. Is there any 
shortcuts that may be taken here?

Thanks for your help,

Joh

On Saturday 29 November 2008 19:06:33 Matthias Kohl wrote:
> to make the use of ROptRegTS and RobRex a little bit simpler at least
> with respect to installation, I introduced the package ROptEstOld on
> R-Forge. So, for the moment one should install ROptEstOld, ROptRegTS and
> RobRex via R-Forge by using (after they are built on R-Forge, which
> should be tomorrow)
>
> install.packages("RobRex", repos="http://R-Forge.R-project.org")
>
> Best,
> Matthias
>
> Johannes Graumann wrote:
> > Thanks for your help. It will take until next week to look into this
> > and get back.
> >
> > Joh
> >
> > On Fri, Nov 28, 2008 at 11:34 AM, Matthias Kohl
> >
> > <Matthias.Kohl using stamats.de> wrote:
> >> Dear Joh,
> >>
> >> in case of our packages ROptEst and RobLox we recently implemented the
> >> functions roptest and roblox, which enable the computation of (in our
> >> sense) optimally robust estimators via one single function.
> >>
> >> In case of our regression packages we do not have such functions so far.
> >> However, we plan to implement these functions in the near future also
> >> using the formula interface of R. For the time being you have to do the
> >> necessary steps by hand.
> >>
> >> After the installation of these packages, you should find a subfolder
> >> "scripts" in the package folders of ROptEst, ROptRegTS and RobRex, as
> >> well as a folder "tests" in case of package RobLox. These folders
> >> contain several examples how to use these packages.
> >>
> >> Let us for instance consider a regression of the form y ~ x.
> >>
> >> Some points you should think about are:
> >> What error distribution do you assume? If normal, go for package RobRex.
> >> If something different, go for package ROptRegTS.
> >> May x and y both be contaminated or only y?
> >>
> >> Two examples using RobRex ...
> >>
> >> ########################################################################
> >>####### ## Example 1
> >> ########################################################################
> >>####### require(MASS)
> >> require(robustbase)
> >> library(ISwR)
> >> data(thuesen)
> >> attach(thuesen)
> >>
> >> ## LS-estimator
> >> fit.LS <- lm(short.velocity ~ blood.glucose)
> >> ## M-estimator
> >> fit.M <- rlm(short.velocity ~ blood.glucose)
> >> ## MM-estimator
> >> fit.MM <- lmrob(short.velocity ~ blood.glucose)
> >> ## LTS-estimator
> >> fit.LTS <- ltsReg(short.velocity ~ blood.glucose)
> >>
> >> ## AL-estimators
> >> ## regressor distribution: design measure
> >> require(RobRex)
> >> K <- DiscreteMVDistribution(cbind(1,blood.glucose))
> >> ## ALc-estimator: conditional neighborhood; i.e., only y is contaminated
> >> ## about 10 sec. on my system
> >> system.time(IC1 <- rgsOptIC.ALc(r = 0.5, K = K, theta = fit.M$coeff,
> >> scale = fit.M$s))
> >> ALc1 <- oneStepEstimator(cbind(1,as.matrix(thuesen)), IC1,
> >> c(fit.M$coeff, fit.M$s))
> >> ## AL-estimator: unconditional neighborhood; i.e., x and y are
> >> contaminated ## about 85 sec. on my system
> >> system.time(IC2 <- rgsOptIC.AL(r = 0.5, K = K, theta = fit.MM$coeff,
> >> scale = fit.MM$s))
> >> AL1 <- oneStepEstimator(cbind(1,as.matrix(thuesen)), IC2,
> >> c(fit.MM$coeff, fit.MM$s))
> >>
> >> ## Plot
> >> require(RColorBrewer)
> >> myCol <- brewer.pal(6, "Set1")
> >> plot(short.velocity ~ blood.glucose, ylab = "fasting blood glucose
> >> [mmol/l]",
> >>   xlab = "mean circumferential shortening velocity [%/s]",
> >>   main = "Ventricular shortening velocity", pch = 20)
> >> abline(fit.LS, lwd = 2, col = myCol[1])
> >> abline(fit.M, lwd = 2, col = myCol[2])
> >> abline(fit.MM, lwd = 2, col = myCol[3])
> >> abline(fit.LTS, lwd = 2, col = myCol[4])
> >> lines(c(1, c(blood.glucose,25)), ALc1[1] +
> >> ALc1[2]*c(1,c(blood.glucose,25)), col = myCol[5], lwd = 2)
> >> lines(c(1, c(blood.glucose,25)), AL1[1] +
> >> AL1[2]*c(1,c(blood.glucose,25)), col = myCol[6], lwd = 2)
> >> legend("topleft", legend = c("LS", "M", "MM", "LTS", "ALc", "AL"),
> >>     fill = myCol, ncol = 2)
> >> detach(thuesen)
> >>
> >> ########################################################################
> >>####### ## Example 2
> >> ########################################################################
> >>####### data(phones)
> >> attach(phones)
> >>
> >> ## LS estimator
> >> fit2.LS <- lm(calls ~ year)
> >> ## M estimator
> >> fit2.M <- rlm(calls ~ year, maxit = 50)
> >> ## MM estimator
> >> fit2.MM <- lmrob(calls ~ year)
> >> ## LTS estimator
> >> fit2.LTS <- ltsReg(calls ~ year)
> >>
> >> ## AL estimators
> >> ## regressor distribution: design measure
> >> K <- DiscreteMVDistribution(cbind(1,year))
> >> ## ALc estimator: only y contaminated
> >> system.time(IC1 <- rgsOptIC.ALc(r = 0.5, K = K, theta = fit2.M$coeff,
> >> scale = fit2.M$s))
> >> ## takes about 9 sec. on my system
> >> ALc2 <- oneStepEstimator(cbind(1,year,calls), IC1, c(fit2.M$coeff,
> >> fit2.M$s))
> >> ## AL estimator: x and y contaminated
> >> system.time(IC2 <- rgsOptIC.AL(r = 0.5, K = K, theta = fit2.MM$coeff,
> >> scale = fit2.MM$s))
> >> ## takes about 80 sec. on my system
> >> AL2 <- oneStepEstimator(cbind(1,year,calls), IC2, c(fit2.MM$coeff,
> >> fit2.MM$s))
> >>
> >> ## Plot
> >> plot(calls ~ year, ylab = "phone calls [Mio.]", xlab = "year",
> >>   main = "Belgium Phone Calls 1950-1973", pch = 20)
> >> abline(fit2.LS, lwd = 2, col = myCol[1])
> >> abline(fit2.M, lwd = 2, col = myCol[2])
> >> abline(fit2.MM, lwd = 2, col = myCol[3])
> >> abline(fit2.LTS, lwd = 2, col = myCol[4])
> >> lines(c(1, c(year,75)), ALc2[1] + ALc2[2]*c(1,c(year,75)), col =
> >> myCol[5], lwd = 2)
> >> lines(c(1, c(year,75)), AL2[1] + AL2[2]*c(1,c(year,75)), col = myCol[6],
> >> lwd = 2)
> >> legend("topleft", legend = c("LS", "M", "MM", "LTS", "ALc", "AL"),
> >>     fill = myCol, ncol = 2)
> >>
> >> #########################################################
> >>
> >> Like in case of RobLox there will be changes to RobRex in the near
> >> future which will clearly speed up these computations ...
> >>
> >> By the way, I made some further tests ...
> >> Using ROptEst version 0.5 (from CRAN archive) and the recent versions of
> >> distr (2.0.3), distrEx (2.0.3) and RandVar (0.6.6), the recent versions
> >> (0.6.1, available from RForge) of ROptRegTS and RobRex install and check
> >> without problems on my system (R version 2.8.0 Patched (2008-11-26
> >> r47022), i686-pc-linux-gnu). I'm just about to submit the new versions
> >> of our distr-family as well as the new versions of RandVar, RobAStBase,
> >> ROptEst and RobLox to CRAN. Because of the incompatibility of ROptRegTS
> >> and RobRex with the new implementation one has to download the current
> >> versions of ROptRegTS and RobRex from R-Forge.
> >>
> >> Best,
> >> Matthias
> >>
> >> Johannes Graumann wrote:
> >>> Yes, fresh R session (see below). Whether it's working? I was looking
> >>> for a function straight forward to use - along the lines of "roblox" -
> >>> but failed. Can you give a hint on how to actually set up something
> >>> mimicking library(robustbase)
> >>> (regression <- lmrob(
> >>>  y~x
> >>> ))
> >>>
> >>> I have had very good results using "roblox" in the past and was
> >>> interested in trying the regression based on the same methodology, but
> >>> being a user and no specialist the package has me intimidated.
> >>>
> >>> Joh
> >>>
> >>>> sessionInfo()
> >>>
> >>> R version 2.8.0 (2008-10-20) x86_64-pc-linux-gnu
> >>> locale:
> >>> LC_CTYPE=en_US.UTF-8; <CUT>
> >>>
> >>> attached base packages:
> >>>  [1] stats4    tcltk     tools     stats     graphics  grDevices utils
> >>>   [8] datasets  methods   base
> >>> other attached packages:
> >>>  [1] ROptRegTS_0.6.0        distrMod_2.0.2         MASS_7.2-44
> >>>  [4] ROptEst_0.5.0          RandVar_0.6.5          distrEx_2.0.2
> >>>  [7] evd_2.2-4              distr_2.0.2           
> >>> SweaveListingUtils_0.1 [10] sfsmisc_1.0-6          startupmsg_0.5.2    
> >>>   robustbase_0.4-3 [13] RColorBrewer_1.0-2     geneplotter_1.20.0    
> >>> annotate_1.20.1 [16] xtable_1.5-4           lattice_0.17-17       
> >>> MaxQuantUtils_1.17 [19] tkrplot_0.0-18         TeachingDemos_2.3     
> >>> plotrix_2.5 [22] gsubfn_0.3-7           proto_0.3-8           
> >>> AnnotationDbi_1.3.12 [25] RSQLite_0.7-1          DBI_0.2-4             
> >>> Biobase_2.1.7 [28] rkward_0.4.9
> >>> loaded via a namespace (and not attached):
> >>> [1] grid_2.8.0         KernSmooth_2.22-22 RobAStBase_0.1.2
> >>>
> >>> On Wednesday 26 November 2008 19:32:47 Matthias Kohl wrote:
> >>>> Dear Joh,
> >>>>
> >>>> was this a fresh R session?
> >>>>
> >>>> I just removed version 0.6 of package ROptEst and let the rest of the
> >>>> packages unchanged. Then, installed version 0.5 of ROptEst and after
> >>>> that installed version 0.5 of package ROptRegTS (from CRAN). Despite
> >>>> some warnings and notes during installation, all seems to work fine
> >>>> ...
> >>>>
> >>>> Does ROptRegTS work on your system?
> >>>>
> >>>> Best,
> >>>> Matthias
> >>>>
> >>>> Johannes Graumann wrote:
> >>>>> ROptEst 0.5! Not ROptRegTS! Sorry.
> >>>>>
> >>>>> Joh
> >>>>>
> >>>>> Johannes Graumann wrote:
> >>>>>> Hello Matthias,
> >>>>>>
> >>>>>> ROptRegTS 0.5 installs fine on top of the most recent rest of the
> >>>>>> bundle
> >>>>>> from R-Forge. When loading it I get the warnings below. Whether the
> >>>>>> functionality is impeded will be figured out later today.
> >>>>>>
> >>>>>> Thanks for your help!
> >>>>>>
> >>>>>> Joh
> >>>>>>
> >>>>>>> warnings()
> >>>>>>
> >>>>>> Warning messages:
> >>>>>> 1: In fun(...) ... : no valid postscript previewer found; consider
> >>>>>> setting options("eps_view"=  "....")        yourself
> >>>>>> 2: Multiple methods tables found for 'optIC'
> >>>>>> 3: Multiple methods tables found for 'neighbor<-'
> >>>>>> 4: Multiple methods tables found for 'CallL2Fam<-'
> >>>>>> 5: Multiple methods tables found for 'generateIC'
> >>>>>> 6: Multiple methods tables found for 'checkIC'
> >>>>>> 7: Multiple methods tables found for 'clip'
> >>>>>> 8: Multiple methods tables found for 'clip<-'
> >>>>>> 9: Multiple methods tables found for 'cent'
> >>>>>> 10: Multiple methods tables found for 'cent<-'
> >>>>>> 11: Multiple methods tables found for 'stand'
> >>>>>> 12: Multiple methods tables found for 'stand<-'
> >>>>>> 13: Multiple methods tables found for 'lowerCase'
> >>>>>> 14: Multiple methods tables found for 'lowerCase<-'
> >>>>>> 15: Multiple methods tables found for 'neighborRadius'
> >>>>>> 16: Multiple methods tables found for 'neighborRadius<-'
> >>>>>> 17: Multiple methods tables found for 'clipLo'
> >>>>>> 18: Multiple methods tables found for 'clipLo<-'
> >>>>>> 19: Multiple methods tables found for 'clipUp'
> >>>>>> 20: Multiple methods tables found for 'clipUp<-'
> >>>>>> 21: Multiple methods tables found for 'L2deriv'
> >>>>>> 22: Multiple methods tables found for 'FisherInfo'
> >>>>>> 23: Multiple methods tables found for 'checkL2deriv'
> >>>>>>
> >>>>>> Matthias Kohl wrote:
> >>>>>>> Dear Joh,
> >>>>>>>
> >>>>>>> we are currently restructuring and extending our packages.
> >>>>>>>
> >>>>>>> Some parts of the package ROptEst (version 0.5) are now included in
> >>>>>>> the
> >>>>>>> new packages distrMod and RobAStBase. Unfortunatelly, the structure
> >>>>>>> of the packages ROptRegTS and RobRex has not been updated yet.
> >>>>>>> Hence, if you want to use package ROptRegTS you have to use the old
> >>>>>>> version (i.e., version 0.5) of ROptEst from the archive
> >>>>>>> (http://cran.at.r-project.org/src/contrib/Archive/ROptEst).
> >>>>>>>
> >>>>>>> These old versions of the packages ROptEst and ROptRegTS should
> >>>>>>> work with R 2.8.0 and the recent versions of the packages distr,
> >>>>>>> distrEx and
> >>>>>>> RandVar. I will check this later today and will then give you more
> >>>>>>> details on this.
> >>>>>>>
> >>>>>>> Best
> >>>>>>> Matthias
> >>>>>>>
> >>>>>>> Johannes Graumann wrote:
> >>>>>>>> Hello,
> >>>>>>>>
> >>>>>>>> Trying to say "library(ROptRegTS)", I get the error below. Can
> >>>>>>>> anyone help me pinpoint what's wrong?
> >>>>>>>>
> >>>>>>>> Thanks, Joh
> >>>>>>>>
> >>>>>>>> Error in loadNamespace(package, c(which.lib.loc, lib.loc),
> >>>>>>>> keep.source
> >>>>>>>> = keep.source) :
> >>>>>>>>  in 'ROptRegTS' methods for export not found: neighbor, bound,
> >>>>>>>> Curve, CallL2Fam
> >>>>>>>> In addition: Warning message:
> >>>>>>>> In fun(...) : no valid postscript previewer found; consider
> >>>>>>>> setting options("eps_view"=  "....")      yourself
> >>>>>>>> Error: package/namespace load failed for 'ROptRegTS'
> >>>>>>>>
> >>>>>>>> _______________________________________________
> >>>>>>>> R-SIG-Robust using r-project.org mailing list
> >>>>>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-robust
> >>>>>
> >>>>> _______________________________________________
> >>>>> R-SIG-Robust using r-project.org mailing list
> >>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-robust
> >>
> >> --
> >> Dr. Matthias Kohl
> >> www.stamats.de


-------------- next part --------------
A non-text attachment was scrubbed...
Name: signature.asc
Type: application/pgp-signature
Size: 835 bytes
Desc: This is a digitally signed message part.
URL: <https://stat.ethz.ch/pipermail/r-sig-robust/attachments/20081201/82f343ba/attachment.sig>


More information about the R-SIG-Robust mailing list