Somewhere I heard that Kolmogorov Smirnov test depends on number of parameters, is true?

If yes, so I have problem because I have used ks.test(...) in R for normal distribution with 2 parameters and for asymetric Laplac distribution with 3 parameters. And then I wolud like to compare each testing statistic $D$.

If KS test depends on number of parameters, there is some package which taken into account this fact? I have been trying found something on net but I have not been successful. Any help will be appreciated, thanks.

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    $\begingroup$ Numerous posts on site discuss this test and the fact that the test assumes a completely specified distribution, and address some of your other issues. For example see here, and here and here - and many more besides; try the search facilities. $\endgroup$ – Glen_b Mar 20 '19 at 15:20
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    $\begingroup$ After reading some of the previous discussions you may want to revise your question. $\endgroup$ – Glen_b Mar 20 '19 at 15:20
  • $\begingroup$ I have already read some of this discusion, so it means that if parameters are known the ks test works properly irrespective of number of parameters of distribution. Thanks $\endgroup$ – Waney Mar 20 '19 at 15:34
  • $\begingroup$ It would be rare for anyone to know the parameters of a Laplace distribution. More common would be that they have been estimated from previous data. That's not the same as knowing them! You would need a two-sample version of the K-S test in that circumstance. $\endgroup$ – whuber Mar 20 '19 at 16:20
  • $\begingroup$ @Waney yes, for example if you have hypothesized population parameters for all the parameters, it doesn't matter how many there were, the distribution is now fully specified $\endgroup$ – Glen_b Mar 20 '19 at 23:52

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