edftest |

Computes goodness-of-fit tests based on the empirical distribution function.

Syntax

series_name.edftest(options)

Options

General Options

dist=arg (default=”nomal”) | Distribution to test: “normal” (Normal distribution), “chisq” (Chi-square distribution), “exp” (Exponential distribution), “xmax” (Extreme Value - Type I maximum), “xmin” (Extreme Value Type I minimum), “gamma” (Gamma), “logit” (Logistic), “pareto” (Pareto), “uniform” (Uniform). |

p1=number | Specify the value of the first parameter of the distribution (as it appears in the dialog). If this option is not specified, the first parameter will be estimated. |

p2=number | Specify the value of the second parameter of the distribution (as it appears in the dialog). If this option is not specified, the second parameter will be estimated. |

p3=number | Specify the value of the third parameter of the distribution (as it appears in the dialog). If this option is not specified, the third parameter will be estimated. |

prompt | Force the dialog to appear from within a program. |

p | Print test results. |

Estimation Options

The following options apply if iterative estimation of parameters is required:

b | Use Berndt-Hall-Hall-Hausman (BHHH) algorithm. The default is Marquardt. |

m=integer | Maximum number of iterations. |

c=number | Set convergence criterion. The criterion is based upon the maximum of the percentage changes in the scaled coefficients. |

showopts / ‑showopts | [Do / do not] display the starting coefficient values and estimation options in the estimation output. |

s | Take starting values from the C coefficient vector. By default, EViews uses distribution specific starting values that typically are based on the method of the moments. |

Examples

x.edftest

uses the default settings to test whether the series x comes from a normal distribution. Both the location and scale parameters are estimated from the data in X.

freeze(tab1) x.edftest(type=chisq, p1=5)

tests whether the series x comes from a distribution with 5 degrees of freedom. The output is stored as a table object TAB1.

Cross-references

See
“Empirical Distribution Tests” for a description of the goodness-of-fit tests.

See also
qqplot.