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csgillespie / poweRlaw

This package implements both the discrete and continuous maximum likelihood estimators for fitting the power-law distribution to data. Additionally, a goodness-of-fit based approach is used to estimate the lower cutoff for the scaling region.
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bootstrap_p ignores m$xmin: bug or feature? #22

Closed linzhp closed 10 years ago

linzhp commented 10 years ago

It seems that bootstrap_p ignores m$xmin and estimates xmin on its own. Is this a bug or feature?

csgillespie commented 10 years ago

I don't think it's a feature or a bug.

When running bootstrap_p we have generated new data. Of course, m$xmin will give you a clue what the value xmin will be, but we still need to estimate it.

The user could use the value of m$xmin to set reasonable bounds on the xmin parameter scan, i.e.

xmins = m$xmin + (-50:50)
bootstrap_p(m, xmin = xmins)