test: Test residuals for stationarity and randomness
In itsmr: Time Series Analysis Using the Innovations Algorithm
test R Documentation
Test residuals for stationarity and randomness
Description
Test residuals for stationarity and randomness
Usage
test(e)
Arguments
e
Time series data (typically residuals from Resid)
Details
Plots ACF, PACF, residuals, and QQ.
Displays results for Ljung-Box, McLeod-Li, turning point,
difference-sign, and rank tests.
The plots can be used to check for stationarity and the
other tests check for white noise.
Value
None
See Also
Resid
Examples
M = c("log","season",12,"trend",1)
e = Resid(wine,M)
test(e) ## Is e stationary?
a = arma(e,1,1)
ee = Resid(wine,M,a)
test(ee) ## Is ee white noise?
itsmr documentation built on Aug. 6, 2022, 9:08 a.m.
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| test | R Documentation |
Test residuals for stationarity and randomness
Description
Test residuals for stationarity and randomness
Usage
test(e)
Arguments
e |
Time series data (typically residuals from |
Details
Plots ACF, PACF, residuals, and QQ. Displays results for Ljung-Box, McLeod-Li, turning point, difference-sign, and rank tests. The plots can be used to check for stationarity and the other tests check for white noise.
Value
None
See Also
Resid
Examples
M = c("log","season",12,"trend",1)
e = Resid(wine,M)
test(e) ## Is e stationary?
a = arma(e,1,1)
ee = Resid(wine,M,a)
test(ee) ## Is ee white noise?
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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