search for: prewhiten

HI all., I have some univariate time series that need to be prewhitened. HOw this can be performed in R. I am thinking of to fit an ARIMA model and substract this from the original series. Is this the correct way THanks in advance nuncio -- Nuncio.M Research Scientist National Center for Antarctic and Ocean research Head land Sada Vasco da Gamma Goa-403804 [[alte...

Hi R users, I am doing cross correlation analysis on 2 time series (call them y-series and x-series) where I need the use the model developed on the x-series to prewhiten the yseries.. Can someone point me to a function/filter in R that would allow me to do that? Thanks in advance for any help! -- View this message in context: http://www.nabble.com/Whitening-Time-Series-tp22041765p22041765.html Sent from the R help mailing list archive at Nabble.com.

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]]

Dear R-help, How could a cross-correlation plot be optimized such that the relationship between seasonal time-series can be studied? We are working with strong seasonal time-series and derived a cross-correlation plot to study the relationship between time-series. The seasonal variation however strongly influences the cross-correlation plot and the plot seems to be ?rather? symmetrical (max

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 idea of specifying my choice of overlapping periods. for me, the need often a...

...ct of a unit change in the predictor series on teh outcome series. These weights are initally estimated by a cross-correlation function (CCF), which assess the relationship between the de=trended predictor series on the de=trended outcome series (with autocorrelation influences removed, called prewhitening)." Is this a reasonable approach to our question? Hints on how to proceed are most welcome, and/or references to papers or texts which might render us a bit less clueless wrt this problem. Regards, Tim C -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-...

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

...(x, y, xlabel, ylabel, log) : 'x' and 'y' lengths differ. I try this code: library(dplR) df.rwi <- detrend(rwl = df, method = "Spline",nyrs=NULL) write.table(df.rwi,file="rwi.txt",quote=FALSE,row.names=TRUE) df.crn <- chron(df.rwi, prefix = "RGE",prewhiten = TRUE) write.table(df.crn,file="crn.txt",quote=FALSE,row.names=TRUE) ##confidence interval library(boot) ci.func <- function(y) { y <- y[!is.na(y)] mean.fun <- function(y,i) { m <- mean(y[i]) n <- length(i) v <- (n-1)*var(y[i])/n^2 c(m,v) } y.b...