View source: R/mixed.frequency.R
HarveyCumulator | R Documentation |
Given a state space model on a fine scale, the Harvey cumulator aggregates the model to a coarser scale (e.g. from days to weeks, or weeks to months).
HarveyCumulator(fine.series,
contains.end,
membership.fraction)
fine.series |
The fine-scale time series to be aggregated. |
contains.end |
A logical vector, with length matching
|
membership.fraction |
The fraction of each fine-scale time
observation belonging to the coarse scale time observation at the
beginning of the time interval. For example, if week i started in
March and ended in April, |
Returns a vector containing the course scale partial aggregates
of fine.series
.
Steven L. Scott steve.the.bayesian@gmail.com
Harvey (1990), "Forecasting, structural time series, and the Kalman filter", Cambridge University Press.
Durbin and Koopman (2001), "Time series analysis by state space methods", Oxford University Press.
bsts.mixed
,
data(goog)
days <- factor(weekdays(index(goog)),
levels = c("Monday", "Tuesday", "Wednesday",
"Thursday", "Friday"),
ordered = TRUE)
## Because of holidays, etc the days do not always go in sequence.
## (Sorry, Rebecca Black! https://www.youtube.com/watch?v=kfVsfOSbJY0)
## diff.days[i] is the number of days between days[i-1] and days[i].
## We know that days[i] is the end of a week if diff.days[i] < 0.
diff.days <- tail(as.numeric(days), -1) - head(as.numeric(days), -1)
contains.end <- c(FALSE, diff.days < 0)
goog.weekly <- HarveyCumulator(goog, contains.end, 1)
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