aggts function

Non-overlapping temporal aggregation of a time series

Non-overlapping temporal aggregation of a time series according to a specific aggregation order.

aggts(y, agg_order, tew = "sum", align = "end", rm_na = FALSE)

Arguments

• y: Univariate or multivariate time series: a vector/matrix or a ts object.
• agg_order: A numeric vector with the aggregation orders to consider.
• tew: A string specifying the type of temporal aggregation. Options include: "sum" (simple summation, default), "avg" (average), "first" (first value of the period), and "last" (last value of the period).
• align: A string or a vector specifying the alignment of y. Options include: "end" (end of the series, default), "start" (start of the series), an integer (or a vector of integers) indicating the starting period of the temporally aggregated series.
• rm_na: If TRUE the missing values are removed.

Returns

A list of vectors or ts objects.

Examples

# Monthly time series (input vector)
y <- ts(rnorm(24), start = 2020, frequency = 12)
# Quarterly time series
x1 <- aggts(y, 3)
# Monthly, quarterly and annual time series
x2 <- aggts(y, c(1, 3, 12))
# All temporally aggregated time series
x3 <- aggts(y)

# Ragged data
y2 <- ts(rnorm(11), start = c(2020, 3), frequency = 4)
# Annual time series: start in 2021
x4 <- aggts(y2, 4, align = 3)
# Semi-annual (start in 2nd semester of 2020) and annual (start in 2021) time series
x5 <- aggts(y2, c(2, 4), align = c(1, 3))

See Also

Utilities: FoReco2matrix(), balance_hierarchy(), commat(), csprojmat(), cstools(), ctprojmat(), cttools(), df2aggmat(), lcmat(), recoinfo(), res2matrix(), shrink_estim(), teprojmat(), tetools(), unbalance_hierarchy()