rdf: Regression in domain frequency

In PacoParra/descomponer-1.5: Seasonal Adjustment by Frequency Analysis

Description

Make a Band Spectrum Regression using the comun frequencies in cross-spectrum .

Usage

rdf(y,x)

Arguments

y	a Vector of the dependent variable
x	a Vector of the independent variable

Details

Transforms the time series in amplitude-frequency domain, order the fourier coefficient by the comun frequencies in cross-spectrum, make a band spectrum regresion (Parra, F. ,2013) of the serie y_t and x_t for every set of fourier coefficients, and select the model to pass the Durbin test in the significance chosen.

If not find significance for Band Spectrum Regression, make a OLS.

The generalized cross validation (gcv), is caluculated by: gcv=n*sse/((n-k)^2)

where "sse" is the residual sums of squares, "n" the observation, and k the coefficients used in the band spectrum regression.

Slow computer in time series higher 1000 data.

The output is a data.frame object.

Value

datos$Y	The Y time-serie
datos$X	The X time-serie
datos$F	The time - serie fitted
datos$reg	The error time-serie
Fregresores	The matrix of regressors choosen in frequency domain
Tregresores	The matrix of regressors choosen in time domain
Nregresores	The coefficient number of fourier chosen
sse	Residual sums of squares
gcv	Generalized Cross Validation

References

DURBIN, J., "Tests for Serial Correlation in Regression Analysis based on the Periodogram ofLeast-Squares Residuals," Biometrika, 56, (No. 1, 1969), 1-15.

Engle, Robert F. (1974), Band Spectrum Regression,International Economic Review 15,1-11.

Harvey, A.C. (1978), Linear Regression in the Frequency Domain, International Economic Review, 19, 507-512.

Parra, F. (2014), Amplitude time-frequency regression, (http://econometria.wordpress.com/2013/08/21/estimation-of-time-varying-regression-coefficients/)

Examples

data(PIB)
data(celec)
rdf(celec,PIB)

PacoParra/descomponer-1.5 documentation built on May 6, 2019, 9:07 a.m.