Given a pre-defined calendar and set of groups, the function displays the long-term means which would be used to seasonally adjust the corresponding regressors, as the final value using contrasts is "number of days in the group - long term mean".
Usage
long_term_mean(
calendar,
frequency,
groups = c(1, 2, 3, 4, 5, 6, 0),
holiday = 7
)Arguments
- calendar
The calendar containing the required holidays
- frequency
Frequency of the series, number of periods per year (12,4,3,2..)
- groups
Groups of days. The length of the array must be 7. It indicates to what group each week day belongs. The first item corresponds to Mondays and the last one to Sundays. The group used for contrasts (usually Sundays) is identified by 0. The other groups are identified by 1, 2,... n (<= 6). For instance, usual trading days are defined by c(1,2,3,4,5,6,0), week days by c(1,1,1,1,1,0,0), week days, Saturdays, Sundays by c(1,1,1,1,1,2,0) etc...
- holiday
Day to aggregate holidays with. (holidays are considered as that day). 1 for Monday... 7 for Sunday. Doesn't necessary belong to the 0-group.
Value
returns an object of class c("matrix","array") with the long term means corresponding
to each group/period, starting with the 0-group.
Details
A long-term mean is a probability based computation of the average value for every period in every group. (see references). For monthly regressors there are 12 types of periods (January to December).
Examples
BE <- national_calendar(list(
fixed_day(7,21),
special_day("NEWYEAR"),
special_day("CHRISTMAS"),
special_day("MAYDAY"),
special_day("EASTERMONDAY"),
special_day("ASCENSION"),
special_day("WHITMONDAY"),
special_day("ASSUMPTION"),
special_day("ALLSAINTSDAY"),
special_day("ARMISTICE")))
lt<-long_term_mean(BE,12,
groups = c(1,1,1,1,1,0,0),
holiday = 7)