Performs the Pormanteau Q and Lagrange Multipliers test for homoscedasticity in a univariate stationary process. The null hypothesis (H0), is that the process is homoscedastic.
a numeric vector or an object of the
A character string naming the desired test for checking stationarity. Valid values are
Level of the test, possible values range from 0.01 to 0.1. By default
an integer with the number of used lags.
Several different tests are available:
Performs Portmanteau Q and Lagrange Multiplier tests for the null hypothesis that the residuals of
an ARIMA model are homoscedastic. The ARCH test is based on the fact that if the residuals (defined
e(t)) are heteroscedastic, the squared residuals (e^2[t]) are autocorrelated.
The first type of test is to examine whether the squares of residuals are a sequence of white noise,
which is called the Portmanteau Q test, and similar to the Ljung-Box test on the squared residuals.
alpha = 0.05 is used to select the more likely hypothesis.
a h.test class with the main results of unit root hypothesis test.
Asael Alonzo Matamoros
Engle, R. F. (1982). Auto-regressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica. 50(4), 987-1007.
McLeod, A. I. & W. K. Li. (1984). Diagnostic Checking ARMA Time Series Models Using Squared-Residual Auto-correlations. Journal of Time Series Analysis. 4, 269-273.
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