jd_cholette_multivar: Benchmarking, Multi-variate Cholette algorithm

In nbbrd/jdemetra-jdlight: Basic JDemetra+ toolset for seasonal adjustment

Description

This function benchmarks a list of timeseries against a set of temporal and/or contemporaneous constraints.

Usage

jd_cholette_multivar(xlist,tcvector,ccvector,rho,lambda)

Arguments

xlist	list of named time series
tcvector	character vector of temporal constraints
ccvector	character vector of contemporaneous constraints
rho	auto-regressive parameter (def=1)
lambda	power of the weights applied to the series. 0 for additive, 0.5 for proportional, 1 for multiplicative (def=1)

Value

returns a list of benchmarked timeseries consistent with a given set of constraints

References

Info on JDemetra+, usage and functions :

http://ec.europa.eu/eurostat/cros/content/download_en

Examples

mylist<-list()
for (i in 1:8) {mylist[[paste0("s",i)]]<- assign(paste0("s",i), jd_airline(60))}

temporal <-c("s8=sum(s7)")
contemporaneous <- c("s3=s1+s2","s6=s4+s5")

mylist_benchmarked<- jd_cholette_multivar(mylist,temporal,contemporaneous)

nbbrd/jdemetra-jdlight documentation built on May 21, 2019, 8:38 a.m.