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  2. Bartlett's test - Wikipedia

    en.wikipedia.org/wiki/Bartlett's_test

    The test procedure due to M.S.E (Mean Square Error/Estimator) Bartlett test is represented here. This test procedure is based on the statistic whose sampling distribution is approximately a Chi-Square distribution with ( k − 1) degrees of freedom, where k is the number of random samples, which may vary in size and are each drawn from ...

  3. Breusch–Godfrey test - Wikipedia

    en.wikipedia.org/wiki/Breusch–Godfrey_test

    The Breusch–Godfrey test is a test for autocorrelation in the errors in a regression model. It makes use of the residuals from the model being considered in a regression analysis, and a test statistic is derived from these. The null hypothesis is that there is no serial correlation of any order up to p. [3]

  4. Autocorrelation - Wikipedia

    en.wikipedia.org/wiki/Autocorrelation

    For example, to calculate the autocorrelation of the real signal sequence = (,,) (i.e. =, =, =, and = for all other values of i) by hand, we first recognize that the definition just given is the same as the "usual" multiplication, but with right shifts, where each vertical addition gives the autocorrelation for particular lag values: +

  5. Ljung–Box test - Wikipedia

    en.wikipedia.org/wiki/Ljung–Box_test

    The Ljung–Box test (named for Greta M. Ljung and George E. P. Box) is a type of statistical test of whether any of a group of autocorrelations of a time series are different from zero.

  6. Durbin–Watson statistic - Wikipedia

    en.wikipedia.org/wiki/Durbin–Watson_statistic

    In statistics, the Durbin–Watson statistic is a test statistic used to detect the presence of autocorrelation at lag 1 in the residuals (prediction errors) from a regression analysis. It is named after James Durbin and Geoffrey Watson .

  7. Category:Autocorrelation - Wikipedia

    en.wikipedia.org/wiki/Category:Autocorrelation

    This page was last edited on 9 December 2016, at 14:50 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.

  8. Autoregressive integrated moving average - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_integrated...

    The order p and q can be determined using the sample autocorrelation function (ACF), partial autocorrelation function (PACF), and/or extended autocorrelation function (EACF) method. [10] Other alternative methods include AIC, BIC, etc. [10] To determine the order of a non-seasonal ARIMA model, a useful criterion is the Akaike information ...

  9. Autoregressive conditional heteroskedasticity - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_conditional...

    The lag length p of a GARCH(p, q) process is established in three steps: . Estimate the best fitting AR(q) model = + + + + = + = +. Compute and plot the ...