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  2. 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]

  3. 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: +

  4. 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.

  5. Correlogram - Wikipedia

    en.wikipedia.org/wiki/Correlogram

    A plot showing 100 random numbers with a "hidden" sine function, and an autocorrelation (correlogram) of the series on the bottom. In the analysis of data, a correlogram is a chart of correlation statistics.

  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. Gauss–Markov process - Wikipedia

    en.wikipedia.org/wiki/Gauss–Markov_process

    A stationary Gauss–Markov process with variance (()) = and time constant has the following properties.. Exponential autocorrelation: () = | |.; A power spectral density (PSD) function that has the same shape as the Cauchy distribution: () = +. (Note that the Cauchy distribution and this spectrum differ by scale factors.)

  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. Autocorrelation technique - Wikipedia

    en.wikipedia.org/wiki/Autocorrelation_technique

    The autocorrelation technique is a method for estimating the dominating frequency in a complex signal, as well as its variance. Specifically, it calculates the first two moments of the power spectrum, namely the mean and variance. It is also known as the pulse-pair algorithm in radar theory.