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**Describe the feature you'd like to have**
As discussed in #277, we should have a long term goal of implementing a density estimation API, just as we have a probabilities API.
The reason is th…
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A Kernel density estimation , is a non-parametric method for estimating the **probability density function - PDF** of a Random Variable. Also as a generic EDA approach - the , kernel density plots ar…
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Now we have a forward model $f(\vec{\theta})$ (an NN emulator) which could return the SED of given physical parameters. Then we need to build a neural density estimator to describe the $P(\vec{\theta}…
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MLPack for R is now on CRAN (https://cran.r-project.org/web/packages/mlpack/index.html) and contains an implementation of "density estimation trees" (paper: https://dl.acm.org/doi/abs/10.1145/2020408.…
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### Describe the workflow you want to enable
Kernel density estimates for bounded data are biased near the boundary because probability mass "spills out of the domain". It would be great to add a bou…
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Once we have a density estimate, identifying outliers can be done by picking points that are in regions with low density.
http://www.jmlr.org/papers/volume13/kim12b/kim12b.pdf
http://web.eecs.umich.ed…
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### Subject of the issue
When using **delta_F_inv_cov="LSDI"** while calling **compute_density_BMTI**, an error appears and the call crashes.
### Your environment
colab notebook, python 3.10…
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Started in 91eeaf096da884c3167416dea56ea1610f958a65, but needs some testing because I'm sure I've broken something unexpected.
## No `x`
```
ggplot(faithful, aes(y = waiting)) +
geom_hdr_boxp…
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Either by Monte Carlo simulations or by analyzing video data
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**Describe the solution you'd like**
Histogram estimation is not present in skpro. Implement them from scratch using the conditional density estimate finding the optimal binwidth(h) and find th…