sptd function

Function to do sparse temporal disaggregation from if(!exists(".Rdpack.currefs")) .Rdpack.currefs <-new.env();Rdpack::insert_citeOnly(keys="mosley2021sparse;textual",package="TSdisaggregation",cached_env=.Rdpack.currefs) .

Used in disaggregation.R to find estimates given the optimal rho parameter.

sptd(Y, X, rho, aggMat, aggRatio, adaptive = FALSE)

Arguments

• Y: The low-frequency response series (n_l x 1 matrix).
• X: The high-frequency indicator series (n x p matrix).
• rho: The AR(1) residual parameter (strictly between -1 and 1).
• aggMat: Aggregation matrix according to 'first', 'sum', 'average', 'last' (default is 'sum').
• aggRatio: Aggregation ratio e.g. 4 for annual-to-quarterly, 3 for quarterly-to-monthly (default is 4).
• adaptive: TRUE to use adaptive lasso penalty. FALSE for lasso penalty. Default is FALSE.

Returns

y Estimated high-frequency response series (n x 1 matrix).

betaHat Estimated coefficient vector (p x 1 matrix).

u_l Estimated aggregate residual series (n_l x 1 matrix).

References

if(!exists(".Rdpack.currefs")) .Rdpack.currefs <-new.env();Rdpack::insert_all_ref(.Rdpack.currefs)