similar to: GLS models - bootstrapping

Hello, I am have fitted GLS models to time series data. Now I wish to bootstrap this data to produce confidence intervals for the model. However, because this is time series data, normal bootstrapping is not applicable. Secondly, 'tsboot' appears to only be useful for ar models - and does not seem to be applicable to GLS models. I have written code in R to randomly sample blocks of

I am trying to fit a generalised least squares model using gls in the nlme package. The model seems to fit very well when I plot the fitted values against the original values, and the model parameters have quite narrow confidence intervals (all are significant at p<5%). The problem is that the log likelihood is always given as -Inf. This doesn't seem to make sense because the model

Hello, I have written code to plot an xyplot as follows: library(lattice) xyplot(len~ageJan1|as.factor(cohort),groups=sex,as.table=T,strip=strip.c ustom(bg='white',fg='white'),data=dat, xlab="Age (January 1st)",ylab="Length (cm)",main="Linear models for male and female cod, by cohort",type='p',

Dear All, This is probably a very basic question but: I have plotted a map of the Barents Sea and surrounding coastline using: map('worldHires',ylim=c(50,85),xlim=c(5,65),fill=T,resolution=0) map.axes() map.scale(x=30,metric=T) Next, I imported a shapefile with depth contours for the sea: contours<-read.shape("D://My Documents/BarentsSea.shp",dbf.data=T) (This is in

Dear R-users, I have imported a shapefile with depth contours for a sea: depths<-read.shape("D://My Documents/BarentsSea.shp",dbf.data=T) (This is in mercator projection) **Is there a way to convert this shapefile into a format that it may be plotted on a contour plot?** I wish to add these contours onto a map (already coded using 'maps' package) to map the sea contours

Does anyone know how p-values can be generated if tsboot (stationary bootstrap) for time series is performed? That would be of great help. Thanks a lot for your comments. Markus [[alternative HTML version deleted]]

Dear R-users, tsboot fails when I try to perform a block bootstrap on seaKen (package wq): these commands: require(wq) require(datasets) boot.block.sen <- function(data){seaKen(data)[[1]]} tsboot(sunspot.month, boot.block.sen, R=1999, l=12, sim="fixed") return: Error in seaKen(data) : x must be a 'ts' Any suggestion on how might I change seaKen in order to use it with

I'm trying to bootstrap some regression coefficients so that I can estimate confidence intervals, but boot is not producing results. Can anybody suggest what I'm doing wrong here? > SpecPress <- ts(rnorm(501)) > Returns <- ts(rnorm(501)) > BootData <- data.frame(cbind(SpecPress, Returns)) > boot.specpress <- function(data, indices, maxit=20){ + data <-

Hello everybody, when I create an object of class boot with the function tsboot() from the package boot and try to compute several types of confidence intervals with boot.ci("object of class boot created with tsboot") I obtain the warning message, that "BCa-intervals are not defined for time-series bootstraps". Does that hold in general? Or is it just not defined in

Hi, I'm a new user or R and I try to concatenate a several rows according with the value in a column. this is my data.frame and I want to concatenate my data.frame according with the column "b" and make a new data.frame with the information in the others columns. >table1 a b c d 1 E001234 TSA IP234 like_domain 2

Hi This is my function. It serves an HTML page after the calculations. I'm connecting to a MSSQL DB using pyodbc. def CAPM(self,client): r=self.r cds="1590" bm="20559" d1 = [] v1 = [] v2 = [] print"Parsing GET Params" params=client.g[1].split("&") for items in

Not so much an R question, as a methodology one... Dealing with some reviewers comments, one of the reviewers suggests bootstrapping my group means and standard deviations since 2 of my 3 groups have a small sample size. My data is geochemical data, and a variety of clustering methods finds 3 groups in the data. One group has 50 members, another group has 10 members and another group 12

Wei Liu <wei.liu at kernel.org> writes: > When Linux is running as the root partition, the hypercall page will > have already been setup by Hyper-V. Copy the content over to the > allocated page. And we can't setup a new hypercall page by writing something different to HV_X64_MSR_HYPERCALL, right? > > The suspend, resume and cleanup paths remain untouched because they

Wei Liu <wei.liu at kernel.org> writes: > Microsoft Hypervisor requires the root partition to make a few > hypercalls to setup application processors before they can be used. > > Signed-off-by: Lillian Grassin-Drake <ligrassi at microsoft.com> > Signed-off-by: Sunil Muthuswamy <sunilmut at microsoft.com> > Co-Developed-by: Lillian Grassin-Drake <ligrassi at

Fritz, I have slightly adapted (didn't work before) "tsboot" from the "boot" library to the current time series conventions of R. The following patch will do that. I suggest to apply this patch to the file "boot/R/bootfuns.q" of the "boot" library at CRAN. best Adrian --- bootfuns.orig.q Thu Dec 9 10:07:23 1999 +++ bootfuns.q Thu Dec 9 10:06:51 1999

Fritz, I have slightly adapted (didn't work before) "tsboot" from the "boot" library to the current time series conventions of R. The following patch will do that. I suggest to apply this patch to the file "boot/R/bootfuns.q" of the "boot" library at CRAN. best Adrian --- bootfuns.orig.q Thu Dec 9 10:07:23 1999 +++ bootfuns.q Thu Dec 9 10:06:51 1999

I am trying to analyse a data with gls/lm using the following set of models prcn.0.lm <- lm( log10(Y)~(cond-1)+(cond-1):t ,prcn) prcn.1.gls <- gls( log10(Y)~(cond-1)+(cond-1):t ,prcn,cor=corAR1()) prcn.0.gls <- gls( log10(Y)~(cond-1)+(cond-1):t ,prcn) prcn.1m.gls <- gls( log10(Y)~(cond-1)+(cond-1):t ,prcn,cor=corAR1(),method="ML") I get the following AICs for these models:

Small correction: The last lines should be? ? ? The following packages have unmet dependencies:? ? ?r-base : Depends: r-base-core (>= 3.6.0-2bionic) but it is not going to be installed? ? ? ? ? ? ? Depends: r-recommended (= 3.6.0-2bionic) but it is not going to be installed? ? ? ? ? ? ? Recommends: r-base-html but it is not going to be installed? ? ? ? ? ? ? Recommends: r-doc-html but it is

Hello listmembers, I've been thinking of using gls in the nlme package to test for serial correlation in my data set. I've simulated a sample data set and have found a large discrepancy in the results I get when using the default method REML vs. ML. The data set involves a response that is measured twice a day (once for each level of a treatment factor). In my simulated data set, I

Wei Liu <wei.liu at kernel.org> writes: > On Tue, Sep 15, 2020 at 12:43:18PM +0000, Wei Liu wrote: >> On Tue, Sep 15, 2020 at 12:16:58PM +0200, Vitaly Kuznetsov wrote: >> > Wei Liu <wei.liu at kernel.org> writes: >> > >> > > When Linux runs as the root partition, it will need to make hypercalls >> > > which return data from the