search for: augmentation

All, I'm re-running some analysis that has been augmented with additional data. When I use the exact same code for the augmented data, the behavior of the aggregate function is very strange, viz., one of the resulting variables is now coded as a factor while it was coded as numeric for the original data. Unfortunately, I cannot provide a reproducible code example since it only seems to occur

Hi R users,I have a question about augmented prediction plot (?augPred). The covariate of my data set is c(0, 0.01, 0.1, 1, 10, 100, 1000) and I have fitted a nonlinear mixed effects model.I use plot(augPred(out.nlme....)) to get the augmented prediction plot. However, because the scale of the covariate is too large thus I am not able to see the detail difference at c(0,0.01, 0.1, and 1). Could

Short question: Is it possible to use statistical tests, like the Augmented Dickey-Fuller test, in functions with for-loops? If not, are there any alternative ways to scale measures? Detailed explanation: I am working with time-series, and I want to flag curves that are not stationary and which display pulses, trends, or level shifts. >df DATE ID VALUE2012-03-06 1

Hello all, I found OS X still has one remaining issue in the autotools. OS X does not include pkg-config by default, and whatever mechanism installs it places pkg.m4 in some location among: /opt/local/share/aclocal/pkg.m4 /usr/local/share/aclocal/pkg.m4 PKG_CHECK_MODULES isn't defined if pkg.m4 isn't in /usr/share/aclocal, so ./configure dies without augmenting aclocal's search

...the package "norm". I got some ways with the experiment, following the help file: s <- prelim.norm(as.matrix(myDataSet)) thetahat <- em.norm(s) rngseed(1234567) theta <- da.norm(s, thetahat, steps=20, showits=TRUE) At this stage however I get the following error: Steps of Data Augmentation: 1...2...Error: NA/NaN/Inf in foreign function call (arg 2) This seems strange to me, since the whole purpose of this routine is to work with NA values. So why is it complaining about NA values? After this I got it to work in an unlikely fashion: I first standardized my dataset using scale(). A...

>>>>> "SH" == Scott Hyde <hydes at byuh.edu> >>>>> on Mon, 18 Jun 2007 16:59:00 -1000 (HST) writes: SH> Martin, How does Matrix implement augmented matrices? I SH> tried this and got the expected result: {Replying to R-help, since this question has come up several times } >> V=matrix(1,2,3) >> V=cbind(V,V)

Hello, I want to compute Wainer et al's augmented subscore(2001) using IRT but I can't find any packages or relevant code. There is a 'subscore' package in R, but I think it only gives functions to calculate augmented subscores using CTT(classical test theory). Is there other package or code to compute subscores using IRT? If it is not, is there any plan to develop it in

...one large matrix V, where V has matrices V.i on diagonal. I create each matrix V.i in a for loop (1 to J), so each time I'd like to augment V with the most recently calculated V.i, such that I'll have V after the final iteration of the for loop. question: how to initialize V and do the augmentation. any advice much appreciated. cheers, dave ps - please respond directly to afshar@miami.edu, thanks! [[alternative HTML version deleted]]

The linker is going off in the weeds trying to parse the dwarf unwind info. The CIE has: Leh_frame_common_begin0: .long 0 ## CIE Identifier Tag .byte 1 ## DW_CIE_VERSION .asciz "zLR" ## CIE Augmentation .byte 1 ## CIE Code Alignment Factor .byte 120 ## CIE Data Alignment Factor .byte 16 ## CIE Return Address Column .byte 2 ## Augmentation Size .byte 16 ## LSDA Encoding = pcrel .byte 16...

Dear R users, I have a function (below) which encompasses several tests. However, when I run it, only the output of the last test is displayed. How can I ensure that the function root(var) will run and display the output from all tests, and not just the last one? Thank you, b. root <- function(var) { #---Phillips-Perron PP.test(var, lshort = TRUE) PP.test(var, lshort = FALSE)

This is a follow up to the message I posted 3 days ago about how to estimate mixed ordinal logit models. I hope you don't mind that I am just pasting in the code and comments from an R file for your feedback. Actual estimates are at the end of the post. ### Subject: mixed ordinal logit via "augmented" data setup. ### I've been interested in estimating an ordinal logit model

Dear Users, please help with the following DF test: ===== library(tseries) library(timeSeries) Y=c(3519,3803,4332,4251,4661,4811,4448,4451,4343,4067,4001,3934,3652,3768 ,4082,4101,4628,4898,4476,4728,4458,4004,4095,4056,3641,3966,4417,4367 ,4821,5190,4638,4904,4528,4383,4339,4327,3856,4072,4563,4561,4984,5316 ,4843,5383,4889,4681,4466,4463,4217,4322,4779,4988,5383,5591,5322,5404

Hi, If I type define i32 @main() gc "shadow-stack" { entry: %0 = alloca i8* %1 = call i8* @malloc(i64 1) store i8* %1, i8** %0 call void @llvm.gcroot(i8** %0, i8* null) ret i32 0 } declare i8* @malloc(i64) declare void @llvm.gcroot(i8**, i8*) nounwind in test.ll and then do > llc test.ll > gcc test.s I get the error ld: in

Dear Developers Team, I have two items: 1. wilcox.test with the paired=T option appears to delete zeros before ranking absolute differences. Would it be possible to add the feature of removing zeros after ranking, which is given in Lehmann's Nonparametrics as the preferred choice. See also Pratt (1959), JASA 54, 655-667. It is given in wilcoxsign_test of the coin package as an option

Hi: I've been reading "Computational Methods for Multilevel Modeling" by Pinheiro and Bates, the idea of embedding the technique in my own c-level code. The basic idea is to rewrite the joint density in a form to mimic a single least squares problem conditional upon the variance parameters. The paper is fairly clear except that some important level of detail is missing. For

...The linker is going off in the weeds trying to parse the dwarf unwind info. The CIE has: > > > Leh_frame_common_begin0: > .long 0 ## CIE Identifier Tag > .byte 1 ## DW_CIE_VERSION > .asciz "zLR" ## CIE Augmentation > .byte 1 ## CIE Code Alignment Factor > .byte 120 ## CIE Data Alignment Factor > .byte 16 ## CIE Return Address Column > .byte 2 ## Augmentation Size > .byte 16 ## LSDA Enc...

Le 04/03/2023 ? 01:21, Pavel Krivitsky a ?crit?: > Dear All, > > Currently, list= in base::replace(x, list, value) has to be an index > vector. For me, at least, the most common use case is for list= to be > some simple property of elements of x, e.g., > > x <- c(1,2,NA,3) > replace(x, is.na(x), 0) > > Particularly when using R pipes, which don't allow multiple

I have no idea, but Google pointed me to this https://cran.r-project.org/web/packages/subscore/index.html Hth Ulrik "Hyunju Kim" <asdfg4882 at yonsei.ac.kr> schrieb am Di., 15. Mai 2018, 07:21: > > > > Hello, > > > > I want to compute Wainer et al's augmented subscore(2001) using IRT but I > can't find any packages or relevant code. > >

This could be extended to sub and gsub as well which gsubfn in the gusbfn package already does: library(gsubfn) gsubfn("^..", toupper, c("abc", "xyz")) ## [1] "ABc" "XYz" On Fri, Mar 3, 2023 at 7:22?PM Pavel Krivitsky <p.krivitsky at unsw.edu.au> wrote: > > Dear All, > > Currently, list= in base::replace(x, list, value)

Hi all, Can anyone clear my doubts about what conclusions to take with the following what puts of some time series tests: > adf.test(melbmax) Augmented Dickey-Fuller Test data: melbmax Dickey-Fuller = -5.4075, Lag order = 15, p-value = 0.01 alternative hypothesis: stationary Warning message: p-value smaller than printed p-value in: adf.test(melbmax)