I have a time series with observations that were collected quasi fortnightly over several years. However, there are between 23 and 26 observations per year. The time series is not equidistant, due to bad weather or holidays where no sampling occurred. Is it legitimate to average these observations to obtain a frequency that can be used in a R time series object?
To illustrate, here is some code (time series of pH values in rain water):
Data <- read.table("http://dl.dropbox.com/u/2108381/Data.txt") Data.col <- data.frame(Time = Data[1:122,1], Value = Data[123:244,1]) Dat.num <- as.numeric(Data.col$Value) pH.TimeSeries <- ts(Dat.num, start = c(2006,2), frequency = 24.4) pH.decomp <- decompose(pH.TimeSeries) plot(pH.decomp)
Is it allowed to approach time series analysis like this? Can I make the decomposition like this? And, is it allowed to average the frequencies over the years? The "decompose" plots make sense since there is a seasonal peak and an upward trend in pH in the summer.
Any direct answer to this challenge or linkage to other websites/posts is greatly appreciated. Some google-fu from my side was to no avail. Please let me know if there are ways to improve this question.