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stats (version 3.3.3)

Box.test: Box-Pierce and Ljung-Box Tests

Description

Compute the Box--Pierce or Ljung--Box test statistic for examining the null hypothesis of independence in a given time series. These are sometimes known as ‘portmanteau’ tests.

Usage

Box.test(x, lag = 1, type = c("Box-Pierce", "Ljung-Box"), fitdf = 0)

Arguments

x
a numeric vector or univariate time series.
lag
the statistic will be based on lag autocorrelation coefficients.
type
test to be performed: partial matching is used.
fitdf
number of degrees of freedom to be subtracted if x is a series of residuals.

Value

A list with class "htest" containing the following components:
statistic
the value of the test statistic.
parameter
the degrees of freedom of the approximate chi-squared distribution of the test statistic (taking fitdf into account.
p.value
the p-value of the test.
method
a character string indicating which type of test was performed.
data.name
a character string giving the name of the data.

Details

These tests are sometimes applied to the residuals from an ARMA(p, q) fit, in which case the references suggest a better approximation to the null-hypothesis distribution is obtained by setting fitdf = p+q, provided of course that lag > fitdf.

References

Box, G. E. P. and Pierce, D. A. (1970), Distribution of residual correlations in autoregressive-integrated moving average time series models. Journal of the American Statistical Association, 65, 1509--1526. Ljung, G. M. and Box, G. E. P. (1978), On a measure of lack of fit in time series models. Biometrika 65, 297--303. Harvey, A. C. (1993) Time Series Models. 2nd Edition, Harvester Wheatsheaf, NY, pp. 44, 45.

Examples

Run this code
x <- rnorm (100)
Box.test (x, lag = 1)
Box.test (x, lag = 1, type = "Ljung")

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