nsdiffs | R Documentation |
Functions to estimate the number of differences required to make a given
time series stationary. nsdiffs
estimates the number of seasonal differences
necessary.
nsdiffs(
x,
alpha = 0.05,
m = frequency(x),
test = c("seas", "ocsb", "hegy", "ch"),
max.D = 1,
...
)
x |
A univariate time series |
alpha |
Level of the test, possible values range from 0.01 to 0.1. |
m |
Deprecated. Length of seasonal period |
test |
Type of unit root test to use |
max.D |
Maximum number of seasonal differences allowed |
... |
Additional arguments to be passed on to the unit root test |
nsdiffs
uses seasonal unit root tests to determine the number of
seasonal differences required for time series x
to be made stationary
(possibly with some lag-one differencing as well).
Several different tests are available:
If test="seas"
(default), a measure of seasonal strength is used, where differencing is
selected if the seasonal strength (Wang, Smith & Hyndman, 2006) exceeds 0.64
(based on minimizing MASE when forecasting using auto.arima on M3 and M4 data).
If test="ch"
, the Canova-Hansen (1995) test is used
(with null hypothesis of deterministic seasonality)
If test="hegy"
, the Hylleberg, Engle, Granger & Yoo (1990) test is used.
If test="ocsb"
, the Osborn-Chui-Smith-Birchenhall
(1988) test is used (with null hypothesis that a seasonal unit root exists).
An integer indicating the number of differences required for stationarity.
Rob J Hyndman, Slava Razbash and Mitchell O'Hara-Wild
Wang, X, Smith, KA, Hyndman, RJ (2006) "Characteristic-based clustering for time series data", Data Mining and Knowledge Discovery, 13(3), 335-364.
Osborn DR, Chui APL, Smith J, and Birchenhall CR (1988) "Seasonality and the order of integration for consumption", Oxford Bulletin of Economics and Statistics 50(4):361-377.
Canova F and Hansen BE (1995) "Are Seasonal Patterns Constant over Time? A Test for Seasonal Stability", Journal of Business and Economic Statistics 13(3):237-252.
Hylleberg S, Engle R, Granger C and Yoo B (1990) "Seasonal integration and cointegration.", Journal of Econometrics 44(1), pp. 215-238.
auto.arima
, ndiffs
, ocsb.test
, hegy.test
, and ch.test
nsdiffs(AirPassengers)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.