des_mat_func: This function sets-up the data-based part of the design...

In wiaidp/MDFA: Signalextraction and Forecasting Based on the Multivariate Direct Filter Approach (MDFA)

Description

This function sets-up the data-based part of the design matrix, accounting for i1/i2 constraints (this is the effective design-matrix in the absence of regularization). It is originally written in grand-mean parametrization (which makes it more tedious). Singularities in the case i1=F, i2=T are avoided by ‘displacing’ the constraints by a small number.

Usage

des_mat_func(i2, i1, L, weight_h_exp, weight_constraint, shift_constraint, Lag)

Arguments

i2	Boolean. If T a second-order filter constraint in frequency zero is obtained: time-shift of real-time filter must match target (together with i1 handles integration order two)
i1	Boolean. If T a first-order filter constraint in frequency zero is obtained: amplitude of real-time filter must match weight_constraint (handles integration order one)
L	Filter-length
weight_h_exp	DFT of explanatory variables
weight_constraint	Constraint vector in the case i1==T
shift_constraint	Constraint vector in the case i2==T
Lag	Nowcast (Lag=0), Forecast (Lag<0), Backcast (Lag>0)

Value

des_mat Data-based design matrix

wiaidp/MDFA documentation built on June 26, 2019, 1:07 p.m.