(the region tabularized by Lilliefors).
Lilliefors normality test
1. lillietest irng:=col(b)
2. lillietest irng:=col(b) df:=mydf stat:=s prob:=p
Please refer to the page for additional option switches when accessing the x-function from script
| Display Name |
Variable Name |
I/O and Type |
Default Value |
Description |
|---|---|---|---|---|
| Input | irng |
Input Range |
|
Specify the input data range |
| Statistics | stat |
Output double |
|
The computed statistic of the test |
| Degrees of Freedom | df |
Output double |
|
Degrees of freedom of the test |
| P-value | prob |
Output double |
|
The probability that the null hypothesis is rejected |
The function performs Lilliefors modification of the Kolmogorov-Smirnov test to determine if the null hypothesis of composite normality is a reasonable assumption regarding the population distribution of a random sample X. The Lilliefors test is based on simulation, so the significance level is restricted to (the region tabularized by Lilliefors).
1. lillietest irng:=col(a)
This command will perform Lilliefors test on the first column, then you can type:
lillietest.=
to list the results.
2. lillietest irng:=col(b) stat:=s
This command will do lilliefors test on Col(b) and assign the test statistic value to variable
.
Lilliefors test is adapted from the Kolmogorov-Smirnov test, and the statistics is computed in the same way as that of Kolmogorov-Smirnov test. However, the p-value is estimated by linear interpolation of the Lilliefors's table, and is different from that of Kolmogorov-Smirnov test.
Keywords:degrees of freedom