similar to: Accouting for temporal correlation in linear regression

Dear R-help members, I have a question regarding how to use varComb function to specify a variance function for the "weights" in the gls. I need to fit a linear model with heteroscedasticity. The variance function is exp(c0+nu0*W +nu1*W^2) where W is a covariate. Initially I want to use varFunc to define my own variance function following the instruction in the Pinheiro and Bates

Dear R-help members, I have a question regarding how to use varComb function to specify a variance function for the "weights" in the gls. I need to fit a linear model with heteroscedasticity. The variance function is exp(c0+nu0*W +nu1*W^2) where W is a covariate. Initially I want to use varFunc to define my own variance function following the instruction in the Pinheiro and

Despite lots of investigation, I haven't found any R packages might be suitable for the following problem. I'd be very grateful for suggestions. I have three-way nested data, with a series of measures (obs) taken in quick succession (equal time spacing) from each subject on different days. The measures taken on the same day are temporally correlated, so I'd like to use an AR1

Hello - I'm trying to modify an option for the lme() or nlme() macros. I want to write my own specification for the variance function and am following homework problem 4, Chapter 5, page 268 of Pinheiro and Bates book on mixed effect. I'm up to point where I've created a new class using an existing variance function class, varExp as a template. Next I need to write an

Hi, I am trying to plot the original data with the line of the model using the predict function. I want to add SE to the graph, but not sure how to get them out as the predict function for gls does not appear to allow for SE=TRUE argument. Here is my code so far: f1<-formula(MaxNASC40_50~hu3+flcmax+TidalFlag) vf1Exp<-varExp(form=~hu3) B1D<-gls(f1,correlation=corGaus(form=Lat~Lon,

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

Hello. I am trying my hand at modifying the varFunc class varExp, but I must be missing a step. All I want to do right now is make a working copy of varExp, call it varExp2, and then later change it. coef.varExp2, coef<-.varExp2, and Initialize.varExp2 all seem to work properly after I construct them. I can successfully use the commands: v2 <- varExp2(form = ~age|Sex,fixed =

Hi, I've problems to get accounting information for print jobs. I'm using samba and CUPs on debian etch. For the HP 1320 printer I use this PPD: http://openprinting.org/foomatic-db/db/source/PPD/HP/HP_LaserJet_1320_Series.ppd Which PS print driver do I have to use at windows client side? Thanks, Marcus

Hi List I got following problem: I have an old accounting software. It runs at the moment on a NT4.0 System which access the program itself on a samba share. I tried to get this application running under Linux with wine. When I copy the whole folder from the file server to the local filesystem (ext2), it works well with wine (tested with 20050111 and 20050310). But when I mount the share into my

Hi, I am trying to add multiple variance structures such as the first example below: vf1 <- varComb(varIdent(form = ~1|Sex), varPower()) However my code below will not work can anybody please advise me? VFcomb<-varComb(varExp(form=~depcptwithextybf),varFixed(form=~FebNAO)) also if you have two variables with the same weights function would you write that as:

Dear list, I am trying to replicate an econometrics study that was orginally done in Stata. (Blanton and Blanton. 2009. A Sectoral Analysis of Human Rights and FDI: Does Industry Type Matter? International Studies Quarterley 53 (2):469 - 493.) The model I try to replicate is in Stata given as xtpcse total_FDI lag_total ciri human_cap worker_rts polity_4 market income econ_growth log_trade

Quoting cosmin at speakeasy.net, on Sat, May 20, 2006 at 11:40:06AM -0700: > I did some changes to the rrule.rb. I needed some getters/setters for > each of the attributes from RRULE. Attached is the diff. If it makes > sense to you to be included in the lib, please do so. If you think > it''s worth to be included, I can add more validation to the setters. I

How does one coerce predict.gls to incorporate the fitted correlation structure from the gls object into predictions? In the example below the AR(1) process with phi=0.545 is not used with predict.gls. Is there another function that does this? I'm going to want to fit a few dozen models varying in order from AR(1) to AR(3) and would like to look at the fits with the correlation structure

Hello list, Thank you very much for replying to my earlier questions. I have a few new questions about R plots: Example: tempdata: RDate Price 2009-12-09 12:00 100 2009-12-09 15:00 99 2009-12-09 18:00 102 .... 2009-12-10 8:00 120 2009-12-10 10:00 110 2009-12-10 16:00 105 My code: (RDate already in R date-time class) plot (price~RDate, data=tempdata, "l") axis.POSIXct(1,

Dear lmer users, The experiment includes 15 groups of (3 males and 1 female). The female is characterized by its quality Q1 and Q2. Each male of a group is characterized by the number of MatingAttempts (with Poisson distribution). I want to examine if male mating attempts depend on female quality. I can see from graphic exploration that the within-group heterogeneity of male attempts increases

dear sir/madam, while i am trying to convert the data into timeseries using xts command.i am getting this error. please help me to resolve this issue xts(mydata$MCP, as.Date(rdate, format='%d-%m-%Y') + xts(mydata$MCP, as.Date(rdate, format='%d-%m-%Y') Error: unexpected symbol in: "xts(mydata$MCP, as.Date(rdate, format='%d-%m-%Y') xts"

Hi R-sters, Just wondering what I might be doing wrong. I'm trying to fit a multiple linear regression model, and being ever mindful about the possibilities of autocorrelation in the errors (it's a time series), the errors appear to follow an AR1 process (ar(ts(glsfit$residuals)) selected order 1). So, when I go back and try to do the simultaneous regression and error fit with gls,

I am trying to calculate monthly means by year of phosphates and nitrates from a multi year data set. Can anybody help me out with the most effective way to do this? My data looks like this: Collection_Date                   Test.Name              Value 2000-01-24 17:00:00            Phosphate               0.108 2000-01-24 17:00:00            Nitrate                     0.037 2001-11-12

Hello, my name is Toby, and i live in Sydney Australia. i would like to buy a 25Kg bag of strontium nitrate and have it delivered to an address in sydney. i understand that long distance postage can sometimes be very costly, so can you please give a a quote for the 25Kg bag, plus the postage cost to my address in sydney. thankyou for your time

Hello everybody, I recently wrote a "program" that to generate AR1 time series, here the code: #By Jomopo. Junio-2007, Leioa, Vizcaya #This program to create the AR1 syntetic series (one by one) #Where the mean is zero, but the variance of the serie AR1 and #the coef. of AR1 are be changed. If var serie AR1 = 1 then is standarized! #Final version for AR1 time series program #Mon Jul