similar to: Error in dimnames(x) for Poisson EWMA model

To ensure ewma_read() without a lock returns a valid but possibly out of date average, modify ewma_add() by using ACCESS_ONCE to prevent intermediate wrong values from being written to avg->internal. Suggested-by: Eric Dumazet <eric.dumazet at gmail.com> Signed-off-by: Michael Dalton <mwdalton at google.com> --- lib/average.c | 6 ++++-- 1 file changed, 4 insertions(+), 2

Hi, I've been searching for a solution to this but have come up empty. I would like to suppress the plot creation when using the ewma function in the qcc package. Normally it's just plot = FALSE, but the ewma function doesn't have this option. Anything I'm missing or a work around? Many thanks, Brian Francis Statistician II Charles River Laboratories

Hello, I would like to use the Exponential Weighted Moving Average procedure to get the variance. Is there any R function for doing this? Many thanks. -- View this message in context: http://www.nabble.com/EWMA-procedure-to-forecast-variance-tf4018317.html#a11412324 Sent from the R help mailing list archive at Nabble.com.

I have the ewma function as shown below. I think I copied it from an oldSplus help page on filter and then modified it with a lot of help from Achim. ewma<-function(x,lambda = 1, init = x[1]) { rval<-filter(lambda*coredata(x),filter=(1-lambda),method="recursive",ini t=init) rval<-zoo(coredata(rval),index(x)) rval } It sort of works but , if there are NA values in the input

Hello, I would like to use the function EWMA() in the fMultivar Package and I have a series of data x, which is the returns series. Basically, I would like to get the variance estimation using EWMA. I am trying something like EWMA(x, lambda) and I have a couple of questions: Should x be the returns series or price series in my case? When I get the result, there are the same numbers of data

hi, Could anyone help me in solving the following error: I have 5 stocks returns data (returns) EWMA = matrix(nrow=T,ncol=5) # create a matrix to hold the covariance matrix for each t lambda = 0.94 S<-cov(returns) # initial (t=1) covariance matrix EWMA[1,] = c(S)[c(1,4,2)] ---ERROR # extract the variances and covariancefor (i in 2:T) { # loop

In case more of you come across my request from this morning, I've already gotten several great tips, which I summarize here since one or two of these did not come across R-help as well. A team of fellow political scientists is on this problem like "white-on-rice"! Brandt, Patrick, John T. Williams Benjamin O. Fordham, and Brian Pollins. 2000. "Dynamic Modeling for Persistent