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Perhaps estimating the kernel with the kernel density estimation could provide better results than with an histogram, either in the parametric or non parametric case, as shown in:
https://www.ethz.c…
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We have experienced some issues with statsmodels' KDE implementation (see in-line comments in `ridgeplot._kde.estimate_density_trace()`.
- statsmodels uses scipy under the hood. This could be a goo…
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No. You should not use functions provided in a given library or package that will **significantly simplify** the
algorithms that you are asked to implement in coursework, if that is the case, you w…
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A wishlist for probabilistic regression methods to implement or interface.
This is partly copied from the list I made when designing the R counterpart https://github.com/mlr-org/mlr3proba/issues/32 .…
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(going a bit in circles)
- Bernstein polynomial density estimation is a kind of kernel estimation based on histogram data, or grouped probabilities. domain is interval [0,1] #7296
- in fast kde w…
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The library currently has no support for items like histograms (1D or 2D), bar charts, contour plots, or even regular line plots with error bars.
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This issue can be a collection and discussion of methods we could add to the library at some point, in no particular order :) Feel free to comment with suggestions and if you feel comfortable, you are…
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Y=F(Xi),i=1.2.3.4.5
pdf of Xi is known.Then how to construct PCE through samples of Xi and Y?
I have seen the Data Driven PCE in tourial of Kernel Density Estimation,is this accessiable?
The ge…
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Hello. I'm trying to understand density-ratio estimation including RuLSIF for implementing transition detection w.r.t. smart home data. Thank you for making such useful module.
As written in the Ru…
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Using R function calls such as: density(times), bw.nrd(times), bw.bcv(times), bw.SJ(times), bw.ucv.mod(times) and bw.diggle(X), bw.ppl(X), bw.scott(X), bw.CvL(X), where times is the N-vector of time p…