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

## 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.

## See also

Utilities:
`FoReco2matrix()`

,
`balance_hierarchy()`

,
`commat()`

,
`csprojmat()`

,
`cstools()`

,
`ctprojmat()`

,
`cttools()`

,
`df2aggmat()`

,
`lcmat()`

,
`recoinfo()`

,
`res2matrix()`

,
`shrink_estim()`

,
`teprojmat()`

,
`tetools()`

,
`unbalance_hierarchy()`

## 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))
```