predict {ASSA} | R Documentation |
Forecasting with Singular Spectrum Trendline
Description
Computes a forcasted trendline for time series data using singular spectrum analysis.
Usage
predict(fitted.model, p = 1)
Arguments
fitted.model |
estimated model using the functions in the package. |
p |
the horizon to produce forecasts. |
Details
predict is a wrapper function for predictions from the results of various singular spectrum model fitting functions on the package. The function invokes particular methods which depend on the class of the first argument (i.e. sst,msst, msstc, isst, misst, etc) .
Value
forecast |
Matrix containing in columns the dimensions and in rows the forecasts. |
a |
Parameters corresponding to the linear recurrence formula. |
Author(s)
Gabriel Martos and Miguel de Carvalho
References
de Carvalho, M. and Martos, G. (2020). Brexit: Tracking and disentangling the sentiment towards leaving the EU. International Journal of Forecasting, 36, 1128–1137. de Carvalho, M. and Martos, G. (2020). Modeling Interval Trendlines: Symbolic Singular Spectrum Analysis for Interval Time Series. Submitted (available on arXiv).
See Also
See sst,msst, msstc, isst, misst
for a version of different models.
Examples
## SIMULATED DATA EXAMPLE
set.seed(1)
N <- 500
t <- seq(.01, 5, length = N)
Y <- cbind(t^3 - 9 * t^2 + 23 * t + rnorm(N, 0, 1),
10 * sin(3 * t) / t + rnorm(N, 0, 1))
y <- mtsframe(date = t, Y)
fit <- msst(y)
# Forecasting:
predict(fit, p = 5)$forecast