search for: movingaverag

I am looking for some help at removing low-frequency components from a signal, through Moving Average on a sliding window. I understand thiis is a smoothing procedure that I never done in my life before .. sigh. I searched R archives and found "rollmean", "MovingAverages {TTR}", "SymmetricMA". None of the above mantioned functions seems to accept the smoothing polynomial order and the sliding window with as input parameters. Maybe I am missing something. I wonder whether there is some building blocks in R if not even a function which does it all (...

...ed(object@intensity, windowSize) : wrong embedding dimension Any ideas? This is the code I´ve used: > library("MALDIquant") > library("readMzXmlData") > spec <- mqReadMzXml("/Users/juane/XML/") > spec <- transformIntensity(prueba, sqrt) > movingAverage <- function(y) { return(filter(y, rep(1,5)/5, sides = 2))} > spec <- transformIntensity(spec, movingAverage) > spec <- removeBaseline(spec, method = "SNIP") > peaks <- detectPeaks(spec, SNR = 2) Error en embed(object@intensity, windowSize) : wrong embedding dimen...

...is just the K-step moving average. For example, imagine I had a data.frame called 'sleep' with 'date' as the date (from as.Date()) and 'hours' as the # hours I slept that night, I would love to do something like: qplot(date, hours, data = sleep) + stat_smooth(method = 'movingaverage', k = 7); does such a thing exist? If not, I know the package is extensible, so any guidance as to how make it to do so would be very much appreciated. Thanks, Mike -- View this message in context: http://n4.nabble.com/Moving-Averages-in-ggplot2-tp958867p958867.html Sent from the R help ma...