similar to: Exception while using NeweyWest function with doMC

Hi guyz, I have run my algorithm in R (see http://pastebin.com/q84Tujfg) and got the following error: Error in ar.ols(x, aic = aic, order.max = order.max, na.action = na.action, : 'order.max' must be < 'n.used' I am pretty sure, that the error comes from the NeweyWest function in line 45, as the NeweyWest function uses the ar.ols() function for pre whitening. Does anyone

Dear R-users, I would like to compute a robust covariance matrix of two series of realizations of random variables: ###Begin Example### data <- cbind(rnorm(100), rnorm(100)) model <- lm(data ~ 1) vcov(model) library(sandwich) NeweyWest(model) #produces an error ###End Example### NeweyWest() produces an error but sandwich(), vcovHAC(), kernHAC, weave(),... do not produce any errors. It

Dear all, I am working on a large dataset and need to use biglm() to perform OLS regressions. I have detected significant ARCH effects which I try to account for using the Newey-West correction. So far, I have worked with NeweyWest() in the sandwich package. NeweyWest() however seems to be unable to handle an object of class "biglm". Looking into the code, I figured out that

I want to calculate Newey West robust standard error using NeweyWest. Comparing the results to what I get in STATA, in order to get the same results in I need to specify "prewhite=0". Can someone explain what this prewhite command means? Thanks [[alternative HTML version deleted]]

Hi, this post is about foreach operators, the compiler package and the last update of doMC that includes support for the compiler functionality. I am using a home-made %dopar%-like operator that adds some custom expression to be executed before the foreach loop expression itself (see sample code below). It used to work perfectly with doMC 1.2.1, but with the introduction of the compiler

Hi all, Sometimes I'll find myself "ctrl-c"-ing like a madman to kill some code that's parallelized via foreach/doMC when I realized that I just set my cpu off to do something boneheaded, and it will keep doing that thing for a while. In these situations, since I interrupted its normal execution, foreach/doMC doesn't "clean up" after itself by killing the

Hello, I am trying to run a small example with foreach, but I am having some problems. Here is the code: *library(doMC) registerDoMC() zappa = list() frank = list() foreach (i = 1:4) %dopar% { zappa[[i]] = kmeans (iris[-5],4) frank[[i]] = warnings() }* The code runs without error. However the zappa and frank will be empty lists. If I use regular *for *instead, the list will be filled up

Hi I'm processing sequencing data trying to collapsing the locations of each unique sequence and write the results to a file (as storing that in a table will require 10GB mem at least) so I wrote a function that, given a sequence id, provide the needed line to be stored library(doMC) # load library registerDoMC(12) # assign the Number of CPU

Hi, I want to calculate the t- and p-values for a linear model using the Newey West estimator. I tried this Code and it usually worked just fine: > oberlm <- lm(DYH ~ BIP + Infl + EOil, data=HU_H) > coeftest(oberlm, NeweyWest(oberlm, lag=2)) t test of coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.1509950 0.0743832 2.0300 0.179486 BIP

Thank you very much Steve. Your suggestion works perfectly -- at least with doSEQ, doMC and doMPI. Bests, Renaud On 28/06/2011 15:35, Stephen Weston wrote: > I think that the result of the concatenation should be a call object, > rather than an expression object. How about something along the > lines of: > > '%dopar2%'<- function(obj, ex) { > ex<-

Dear list, I'm just getting started learning how to use remote supercomputers for execution of parallelized code. I got a lot of initial help from this <http://stackoverflow.com/questions/14553357/parallelizing-on-a-supercomputer-and-then-combining-the-parallel-results-r> previous post, as well as one particularly helpful and patient XSEDE guy. I'm only using one node (for the

REvolution Computing has just released three new packages for R to CRAN (under the open-source Apache 2.0 license): foreach, iterators, and doMC. Together, they provide a simple, scalable parallel computing framework for R that lets you take advantage of your multicore or multiprocessor workstation to program loops that run faster than traditional loops in R. The three packages build on each

REvolution Computing has just released three new packages for R to CRAN (under the open-source Apache 2.0 license): foreach, iterators, and doMC. Together, they provide a simple, scalable parallel computing framework for R that lets you take advantage of your multicore or multiprocessor workstation to program loops that run faster than traditional loops in R. The three packages build on each

Dear all, I am converting a large process to a parallel backhend using doMC and foreach. Basically, I havea long list of input graph files and each of them calls soem basic igraph package functions. I am parallelizing the run, in order to save time. All works fine, and each %dopar% call ends with a vector of results that at the end got fed into a data frame and saved as a csv table. When I

dear R experts: ?I am writing my own little newey-west standard error function, with heteroskedasticity and arbitrary x period autocorrelation corrections. ?including my function in this post here may help others searching for something similar. it is working quite well, except on occasion, it complains that Error in solve.default(crossprod(x.na.omitted, x.na.omitted)) : system is

thank you, achim. I will try chol2inv. sandwich is a very nice package, but let me make some short suggestions. I am not a good econometrician, so I do not know what prewhitening is, and the vignette did not explain it. "?coeftest" did not work after I loaded the library. automatic bandwidth selection can be a good thing, but is not always. as to my own little function, I like the

Dear all, I am currently working on a package which involves some simulation where no current simulation run depends on a previous simulation run. That is why I decided to parallelize the computation using the doMC package (which exists only for unix-like OS). I can create a package without any R CMD check and R CMD build errors on my computers (Ubuntu Linux 32bit & 64 bit). The problem

Hi, I would like to estimate a panel model (small N large T, fixed effects), but would need "robust" standard errors for that. In particular, I am worried about potential serial correlation for a given individual (not so much about correlation in the cross section). >From the documentation, it looks as if the vcovHC that comes with plm does not seem to do autocorrelation, and the

Hi, in R 2.12.1, R CMD check hangs when building a vignette that uses a foreach loop with the doMC parallel backend. This does not happen in R 2.13.1, nor if I use doSEQ instead of doMC. All versions of multicore, doMC and foreach are the same on both my R installations. Has anybody encountered a similar issue? Thank you. Renaud ### UNIVERSITY OF CAPE TOWN This e-mail is subject to the

some hints for the search engines. I just did install.packages("foreach") install.packages("doMC") library(doMC) registerDoMC() library(foreach) > foreach(i = 1:3) %dopar% sqrt(i) The process has forked and you cannot use this CoreFoundation functionality safely. You MUST exec(). Break on