Comments (3)
Hi Emanuel,
thanks for reaching out and providing an example with your report.
The reason for this behavior is that the number of observations is too small for this type of model. If you check out our paper, you'll see that the smallest number of observations we consider in our simulations is 250 with a value of alpha of 5%.
With n=100 and alpha=1% you're out of luck here, sorry.
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Sure, I'm glad someone is actually using the package ... ;-). And yes, I meant
Thanks for the hint with the error messages. I think I should indeed add more checks on the input data. Thanks for bringing this up.
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Thanks for the quick reply!
Just to clarify the alpha refers to the probability level τ in the paper, right? So you actually used as the smallest specification n=250 and alpha=0.025 in the MC simulation on page 37 of your paper? Please correct me if I am wrong.
Just as a sidenote I also got the same error for sample sizes close to 300 and the alpha level of 1%. Input checks that trigger more informative error messages would be great in this context.
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