Description Usage Arguments Details Value Author(s) See Also Examples
View source: R/ts.non.seas.decomp.r
Decomposition of time series with no seasonal component using local regression models
1 | ts.non.seas.decomp(tsdata, tojson = FALSE)
|
tsdata |
The input univariate non seasonal time series data |
tojson |
If TRUE the results are returned in json format, default returns a list |
For non-seasonal time series there is no seasonal component. Local regression and likelihood models (locfit package) are used in order to extract the trend and remaider components.
A list with the following components:
stl.plot:
trend The estimated trend component
trend.ci.up The estimated up limit for trend component
trend.ci.low The estimated low limit for trend component
seasonal The estimated seasonal component
remainder The estimated remainder component
time The time of the series was sampled
stl.general:
stl.degree The degree of fit
degfr The effective degrees of freedom
degfr.fitted The fitted degrees of freedom
residuals_fitted:
residuals The residuals of the model (fitted innovations)
fitted The model's fitted values
time the time of tsdata
line The y=0 line
compare:
resid.variance The residuals variance
used.obs The used observations for the fitting
loglik The maximized log-likelihood (of the differenced data), or the approximation to it used
aic The AIC value corresponding to the log-likelihood
bic The BIC value corresponding to the log-likelihood
gcv The generalized cross-validation statistic
Kleanthis Koupidis
ts.analysis
, locfit
,
predict.locfit
1 |
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