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roadmap for parts
#9133
#9148
I still don't have an overview and design for the desired module structure, especially where to put helper functions and model/estimation functions that are reused i…
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# Power Analysis by Data Simulation in R - Part II | Julian Quandt
This part foucuses on simple scenarios (t-tests) to introduce the simulation of correlated measurements and multivariate normal-dist…
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```
What steps will reproduce the problem?
1. load ocaml and hol.ml as usual
2. loadt "Library/analysis.ml";;
3. loadt "Multivariate/vectors.ml";;
What is the expected output? What do you see instead…
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Just realized I misinterpreted the point of #5, so I'm superceding that issue with this one. We should probably have a mechanism for user-defined derivatives that works for n-ary, multivariate functio…
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After #2 is done, update multivariate analysis, some ideas:
* Group by resident times
* SEM based on conceptual model?
* Create cond prob models for sites, time periods, combo of variables when…
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### Is there an existing issue for this?
- [X] I have searched the existing issues for a bug report that matches the one I want to file, without success.
### Did you read the documentation and troub…
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```
sage: from sage.rings.asymptotic.asymptotics_multivariate_generating_functions import FractionWithFactoredDenominatorRing
sage: R. = PolynomialRing(QQ)
sage: FFPD = FractionWithFactoredDenomina…
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## Expected Behavior
Even if the `category_encoders.one_hot.OneHotEncoder` doesn't encode any features, we would expect it to convert a pd.DataFrame into a numpy.ndarray if we set the parameter :
…
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great code thanks
may you clarify :
will it work for multivariate time series prediction both regression and classification
each row means the time series, and columns represent different cont…
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Dear Py-Boost developers,
Thanks for the very interesting paper and for making the code publicly available.
I am the author of [XGBoostLSS](https://github.com/StatMixedML/XGBoostLSS) and [Light…