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Free-choice profiling is a method for determining the quality of a thing by having a large number of subjects experience (view, taste, read, etc.) it and then allowing them to describe the thing in their own words, as opposed to posing them a set of "yes-no-maybe" questions.
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 ...
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]
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 .
Autocorrelation technique; Autocovariance; Autoregressive conditional heteroskedasticity; Autoregressive fractionally integrated moving average; Autoregressive model; Autoregressive moving-average model
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: +
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The Ljung–Box test may be defined as: : The data is not correlated (i.e. the correlations in the population from which the sample is taken are 0, so that any observed correlations in the data result from randomness of the sampling process).