Description Usage Arguments Value
Main estimation routine: Sets-up the generic optimization criteria proposed in MDFA-Legacy project (book)
1 2 3 4 | mdfa_analytic(L, lambda, weight_func, Lag, Gamma, eta, cutoff, i1, i2,
weight_constraint, lambda_cross, lambda_decay, lambda_smooth, lin_eta,
shift_constraint, grand_mean, b0_H0, c_eta, weight_structure, white_noise,
synchronicity, lag_mat, troikaner)
|
L |
Filter-length |
lambda |
Customization parameter: Timeliness is emphasized in the ATS-trilemma if lambda>0 |
weight_func |
DFT-matrix or alternative (for example model-based) estimate: first column is the target variable, additional columns are explanatory variables |
Lag |
Nowcast (Lag=0), Forecast (Lag<0), Backcast (Lag>0) |
Gamma |
Generic target specification: typically symmetric Lowpass (trend) or Bandpass (cycle) filters. Highpass and anticipative allpass (forecast) can be specified too |
eta |
Customization parameter: Smoothness is emphasized in the ATS-trilemma if eta>0 |
cutoff |
Specifies start-frequency in stopband from which Smoothness is emphasized (corresponds typically to the cutoff of the lowpass target). Is not used if eta=0. |
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) |
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) |
weight_constraint |
Constraint vector in the case i1==T |
lambda_cross |
Regularization: cross-sectional term |
lambda_decay |
Regularization: decay term |
lambda_smooth |
Regularization: smoothness term |
lin_eta |
Boolean: impose continuous or discontinuous Smoothness customization |
shift_constraint |
Constraint vector in the case i2==T |
grand_mean |
Boolean: if T then a grand-mean parametrization is imposed (default is F) |
b0_H0 |
Regularization: shrinkage target (arbitrary designs can be replicated by imposing strong regularization) |
c_eta |
Boolean: impose mild/strong smoothness customization (default is F) |
weight_structure |
Add structure to the optimization criterion (default value is weight_structure<-c(0,0): no structure imposed) |
white_noise |
Impose a flat DFT (phase information is maintained) |
synchronicity |
Impose a zero shift across series (amplitude information is maintained) |
lag_mat |
Matrix for implementing effective lags in a mixed-frequency setting |
troikaner |
Boolean: if T then degrees oif freedom will be computed (time-consuming computations if K is large) |
b Matrix of optimal filter coefficients
trffkt Complex transfer function of optimal multivariate filter
rever Criterion value (corresponds to a sample estimate of the MSE if lambda=eta=0)
degrees_freedom Degrees of freedom (when imposing regularization the degrres of freedom are smaller than L times the number of explanatory series)
Accuracy Accuracy term in decomposition of MSE
Smoothness Smoothness term in decomposition of MSE
Timeliness Timeliness term in decomposition of MSE
MS_error Sample estimate of MSE: consistent estimate in the cases lambda>0 and/or eta>0
freezed_degrees_new The complementary of degrees_freedom
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