descomponer (version 1.6)

predictFFF: Prediction whit Regression in FFF

Description

Make a prediction for a rdf object

Usage

predictFFF(y,x,new)

Arguments

y

a Vector of the dependent variable

x

a Vector of the independent variable

new

A data frame in which to look for variables with which to predict. If omitted, the fitted values are used.

Value

fit

vector or matrix as above

Details

Use predict.lm, with interval="confidence"

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.

Gallant; A. R.(1984), The Fourier Flexible Form. Amer. J. Agr. Econ.66(1984):204-15.

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

Parra, F.(2021), Econometria con Series de Fourier (https://econometria.files.wordpress.com/2020/12/curso-de-econometria-avanzado.pdf)

Examples

# NOT RUN {
data("ipi")
t=seq(1:length(ipi))
Mod1=FFF(ipi,t)
plot(ipi)
lines(Mod1$fitted)
new=(length(t)+1):(length(t)+12)
Mod2=predictFFF(ipi,t,new)
# }