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[ENH] Skew-Normal Distribution #512
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Thanks, great start!
Some comments:
- please follow the extension template carefully, all
__init__
parameters should be written toself
, to an attribute of the same name - properties should not be used for the
__init__
parameters, this is due to how the base classget_params
etc works loc
is a reserved attribute and should not be overridden. Another common name isxi
, but feel free to choose anything as lon gas it is notloc
.- code formatting tests are failing, please address
@fkiraly |
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Thanks!
- I do not see a reason to use the
BaseDistribution
, the adapter does the same thing with much less code - kindly ensure code is properly formatted, see https://www.sktime.net/en/stable/developer_guide/coding_standards.html
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Thanks!
Can you kindly make sure you use the extension template? Please read it carefully. For instance:
__init__
parameters should be written to self- the docstring should describe the distribution, see a few other examples in the same folder
- please follow the code formatting guide https://www.sktime.net/en/stable/developer_guide/coding_standards.html
Reference Issues/PRs
Fixes Issue #510
What does this implement/fix? Explain your changes.
This implementation adds a new
Skew-Normal
distribution as a probabilistic model inskpro
. The inspiration comes from the paper (https://www.ine.pt/revstat/pdf/rs130105.pdf).The
Skew-Normal
distribution captures skewness in data, improving the flexibility of predictive distributions. Scipy already implements this asscipy.stats.skewnorm
, which is used as a dependency to avoid redundant code.Key changes include:
SkewNormal
class to the probabilistic module with parameter fitting and density evaluation methods.SkewNormal
.Does your contribution introduce a new dependency?
No new core dependencies are introduced.
scipy
is already a core dependency.