Comments (8)
Yep, I'm already working on it.
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Note that the choice of the number of bins here should be different than a histogram.
In a histogram, you choose the number of bins as a method of avoiding overfitting (i.e. regularization).
For a KDE, the number of bins just affects the numerical resolution of the resulting function, so you want to choose as many as your computational budget allows (up to the resolution of your screen, or whatever needs you have). Ideally it should also be a power of 2 to gain the most advantage from the FFTs. The regularization is handled by the kernel function.
The 2048 was admittedly a pretty arbitrary pick, based on scaling up R's choice (512) by a bit.
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Whenever he is talking to his wife/girlfriend ;)
from kerneldensity.jl.
That seems like a good idea to me. Would you be interested in putting together a PR for this?
from kerneldensity.jl.
Thank for that comments, I haven't noticed that. This ticket seems rather pointless than. Unless there is another reason to do it?
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We could implement a different a more data-aware default than 2048. Perhaps there's some literature around that recommends something along those lines for kernel density estimation rather than histograms?
from kerneldensity.jl.
I think Simon is right, it doesn't seem to make any difference for the resulting density other than sampling.
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I think Simon is right
Agreed. After all, when isn't he right? 😄
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Related Issues (20)
- Lazy evaluation KDE HOT 2
- support sample weights HOT 2
- High Dimensional Kernel Estimation - Tensor Train Estimation HOT 1
- ArgumentError: reducing over an empty collection is not allowed HOT 7
- kde on Vector{Date}
- DocStringsExtensions v0.9 HOT 3
- which is x and which is y?
- Error: Error during loading of extension ChainRulesCoreExt of LogExpFunctions, use `Base.retry_load_extensions()` to retry. HOT 2
- No more type aliases in StatsBase HOT 1
- why permutedims?
- Interface of KernelDensity.pdf is not consistent with Distributions.pdf HOT 3
- Drop FFTW dependency HOT 3
- new method: fastKDE HOT 1
- Bivariate pdf call for list of values
- TagBot trigger issue HOT 8
- Borrow some ideas from GetDist Python package
- Add and subtract kerneldensities HOT 3
- Re-scale data before performing bivariate KDE
- Multivariate KDE support HOT 1
- Replace Juno.progress() in code HOT 1
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