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1

You could take this to extreme and ask why wouldn't we use non-parametric model like $k$-NN regression? Actually, the opposite question Why would anyone use KNN for regression? was asked, and you can check it for more detailed discussion. You can also make the question more broad and ask why wouldn't we use more complicated models instead of simpler ones? ...

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In the wikipedia-definition of the $\chi^2$-distribution (https://en.wikipedia.org/wiki/Chi-squared_distribution), $k$ (the "degrees of freedom") is an integer. However, the distribution itself can be evaluated for non-integer values, too. In your case, your change in deviance is tiny (the value is not actually shown, except that it is less than 0.001), ...

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Questions such as "how good is this fit?" or "What is a reasonable fit?" are field dependent (e.g. we generally get worse fits in psychology than in physics) and, within any field, they can be question dependent. The "rules of thumb" that you cite for linear regression are, I think, too general to be useful. I think what you need to do is look at fitted ...

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This is an old question, but I ran into a similar situation when trying to run a gamm model using bam. I believe what's going on is that s(prev, speaker, bs='re') in the model above is estimating a variance term for the ~prev:speaker-1 interaction (random slopes), whereas s(time, by=speaker, bs="fs", m=1) is estimating a separate slope term for each ...

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Those will be either all the 0s (most likely) or 1s/smallest value in your original data. You don’t say what these data are but as you mentioning fishing outcomes it is highly likely that these have some natural lower bound and this line in the residuals are all the observations that take this lower bound (before transformation). As you don’t exactly what ...

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