similar to: Error Coefficient matrix not invertible using nlme correlation

Dear Rers, I have threes series, x, y, z and I want to fit a model z ~ x + y. First of all, I fit a lm. I found the residuals are correlated, by looking at the acf() and pacf(). Then I tried to fit a gls model allowing residuals to be correlated (correlation = corARMA(p=5, q=1)): y.na <- as.data.frame(y[complete.cases(y),]) y.gls <- gls(z ~ x + y, data = y.na, correlation=corARMA(p=5,

Trying following example from Pinheiro and Bates in order to fit an ARMA(1,1) model: library(nlme) fm1Ovary.lme<-lme(follicles~sin(2*pi*Time)+cos(*pi*Time),data=Ovary,random=p dDiag(~sin(2*pi*Time))) fm5Ovary.lme<-update(fm1Ovary.lme,corr=corARMA(p=1,q=1)) I get follwing error message: Error in "coef<-.corARMA"(`*tmp*`, value = c(62.3428455941166, 62.3428517930051 :

Hi, I am using 2 times series and I want to carry out a regression of Seri1 by Serie2 using structured (autocorrelated) errors. (Equivalent to the autoreg function in SAS) I found the function gls (package nlme) and I made: gls_mens<-gls(mening_s_des~dataATB, correlation = corAR1()) My problem is that I don’t want a AR(1) structure but ARMA(n,p) but the execution fails :

Dear All, I am trying to use the do.call command to avoid tedious loops in R when I need to call repetitively a function. I am experiencing a problem when the arguments of a function are given with a vector (I need to express then this way to be able later on to integrate them numerically with the adapt package). Consider the small script: remove(list=ls()) #library(adapt) # first a list of the

Hi there fellow R-users, I am trying to follow an example of modelling a serial correlation structure in the textbook "Mixed Effects Model in S and Splus". However, I am getting some very odd results. Here is what I am trying to run: library(nlme) data(Ovary) fm1<-lme(follicles~sin(2*pi*Time)+cos(2*pi*Time),data=Ovary,random=pdDiag(~s in(2*pi*Time))) ### The example is fine up

Dear R Community, I am new to R, and have a question that I suspect may be quite simple but is proving a formidable roadblock for me. I have a large data set that includes water-quality measurements collected over many 24-hour periods. The date and time of sample collection are in a combined Date/Time field in the format yyyy-mm-dd hh:mm:ss. I need to be able to subset the data for analysis of

Description of Problem We are rapidly approaching the time of year when some will transition from standard time (ST) to daylight savings time (DST) and others will make the opposite transition. These vernal and autumnal transitions have important implications for those with Microsoft systems and use utilities that compare file timestamps on different filesystem types or with filesystems on other

https://bugzilla.netfilter.org/show_bug.cgi?id=1077 Bug ID: 1077 Summary: New traffic reduces conntrack timeout Product: netfilter/iptables Version: unspecified Hardware: All OS: All Status: NEW Severity: normal Priority: P5 Component: nf_conntrack Assignee: netfilter-buglog

Hi everyone, I downloaded the latest version of LLVM PTX backend from http://www.prog.uni-saarland.de/projects/anysl and made the required changes to all the files mentioned in the README. But I get the following error when I compile it. llvm[3]: Compiling PTXBackend.cpp for Release build In file included from PTXBackend.h:70:0, from PTXBackend.cpp:36: PTXPasses.h: In constructor

Hey everybody, good news for everyone interested in the PTX backend: We decided to release the current source code under the GPL - you can find the latest tarball here: http://www.prog.uni-saarland.de/projects/anysl You will find the README in the attachment, which should hopefully answer a lot of questions concerning the implementation and the current status. If you have further questions,

Dear All, I'd like to know if it is possible to create animations with R. To be specific, I attach a code I am using for my research to plot some analytical results in 3D using the lattice package. It is not necessary to go through the code. Simply, it plots some 3D density profiles at two different times selected by the user. I wonder if it is possible to use the data generated for different

I've looked around but I can't find the method in R for testing whether the resulting estimated coefficients of an AR model imply that the model is invertible. To quote from eric zivot's blue book : " the AR(p) is invertible provided the rots of the characteristic equation Phi(z) = 1 - phi_1*z - phi_2*z^2 = phi_3*z^3 - ..... Phi_p*z^p = 0 lie outside the complex circle".

Dear list, When I read some source code, I find lot of place used symbol <<- , e.g. lastTime <<- newTime; What is the meaning here? Also, I find some method with the name start with dot, e.g. .RowStandardizeCentered = function(x) { div = sqrt( rowSums(x^2) ); div[ div == 0 ] = 1; return( x/div ); } What is the special meaning for the method name start with a dot? Thank you

Recently various needs for multiple version handling were discussed and I put forward a plan of mine. Subsequently the proposal for a --compare-file=<FILE> switch had support, so I have implemented this. I have also implemented an experimental --compare-auto which decides which file to match against using a rule. Instructions for patch: 1. Install rsync-2.5.6 source 2. "patch -p1

I'm working with data measured in a tunnel to estimate the emission factor of heavy & light vehicles. I tried to use 'gnls' and I get the following Error: >> Error in "coef<-.corARMA"(*tmp*, value = c(174.267493382104, 173.412740072763 : >> Coefficient matrix not invertible Here is my R-code: data <- d.plabutsch.neu # calculating the starting

I have a csv file, heartrate excercise medicine Time 12 0 0 4:30 am 23 5 0 5:00 am 34 6 0 5:30 am 56 3 0 6:00 am 24 12

Hello, I have some question on chron I currently doing this t1 <- chron(,"11:30:00") t2 <- chron(,"11:45:00") tt <- seq(t1,t2,by=times("00:00:01")) tt has 901 values (15 minutes * 60 secs) and then x1 <- rnorm(1:901) x2 <- rnorm(1:901) x3 <- rnorm(1:901) df <- data.frame(tt, x1, x2, x3) I would like to write a function such that I can

Hi, I'm a new member here in the list. I am a graduate from University of Georgia. Recently in doing analysis using lme on a dataset, I found several questions: 1. How to express the equation when the correlation structure is very complicated. For exmaple, if the fixed is y(t)=0.03x1(t)+1.5x2(t)(I omitted "hat" and others). And the model with corARMA(p=2,q=3) is proper. What will be

OK, I need help!! I've been searching, but I don't understand the logic of some this dataframe addressing syntax. What is this type of code called? test [["v3"]] [is.na(test[["v2"]])] <-10 #choose column v3 where column v2 is == 4 and replace with 10 and where is it documented? The code below works for what I want to do (find the non-missing value in a row),

I have a data analysis job for which lme may be used. Prof. Spencer Graves had helped me much on that. I'm really appreciated for that. Could anybody else in the list give me some hints from other perspectives? I hope I can learn as much as possible for this complicated real data. Thanks in advance. Hanhan To briefly describe my data: My data is health effect measurements (y) and personal