Description Usage Arguments Details Value Author(s) References See Also Examples
Performs the Lagrange Multipliers test for homoscedasticity in a stationary process. The null hypothesis (H0), is that the process is homoscedastic.
1 | Lm.test(y,lag.max = 2,alpha = 0.05)
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y |
a numeric vector or an object of the |
lag.max |
an integer with the number of used lags. |
alpha |
Level of the test, possible values range from 0.01 to 0.1. By default
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The Lagrange Multiplier test proposed by Engle (1982) fits a linear regression model for the squared residuals and examines whether the fitted model is significant. So the null hypothesis is that the squared residuals are a sequence of white noise, namely, the residuals are homoscedastic.
a h.test class with the main results of the Lagrage multiplier hypothesis test. The h.test class have the following values:
"Lm"The lagrange multiplier statistic
"df"The test degrees freedoms
"p.value"The p value
"alternative"The alternative hypothesis
"method"The used method
"data.name"The data name.
A. Trapletti and 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. and 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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