sptd {DisaggregateTS}R Documentation

Sparse Temporal Disaggregation

Description

This function performs sparse temporal disaggregation as described in Mosley et al. (2022). It estimates the high-frequency response series using LARS (Least Angle Regression) and applies either a LASSO or adaptive LASSO penalty.

Usage

sptd(Y, X, rho, aggMat = "sum", aggRatio = 4, adaptive = FALSE)

Arguments

Y

The low-frequency response series (n_l \times 1 matrix).

X

The high-frequency indicator series (n \times p matrix).

rho

The AR(1) residual parameter (must be strictly between -1 and 1).

aggMat

Aggregation matrix method ('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

Logical. If TRUE, use adaptive LASSO penalty. If FALSE, use standard LASSO penalty. Default is FALSE.

Value

A list containing:

References

Mosley L, Eckley IA, Gibberd A (2022). “Sparse Temporal Disaggregation.” Journal of the Royal Statistical Society Series A: Statistics in Society, 185(4), 2203-2233. ISSN 0964-1998, doi:10.1111/rssa.12952, https://academic.oup.com/jrsssa/article-pdf/185/4/2203/49420183/jrsssa_185_4_2203.pdf.


[Package DisaggregateTS version 3.0.1 Index]