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This method is motivated by Mendelian randomization
https://www.nature.com/articles/s41588-020-0706-2
Could be a possible application candidate for Alzheimer's data-set. We can discuss its model…
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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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Partial list of functions that use legacy `seed` or `random_state` behavior. Per [SPEC 7](https://scientific-python.org/specs/spec-0007/), we're changing the keyword to `rng`.
Generated mostly by s…
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I think we need three cases: single column (checks for NAs, removes from data and tree as needed); pairwise (removes any taxa not present in BOTH, for things like PGLS); and multivariate (removes any …
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Is there any reason that the various DPP types are not subtypes of Multivariate Distribution? This could open open compatibility with the wider julia ecosystem. I might be willing to do the work to ma…
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Hi,
Does Flint have multi-point evaluation of multivariate polynomials at geometric sequences over finite fields ?
For example, something like the matrix-vector product with a transposed Vander…
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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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Multivariate analyses usually work with trials/repetitions. Can you add support for Granger causality `X` and `Y` being either vector (single trial of length `n_time_points`) or matrix of shape `n_tri…
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Multivariate Imputation by Chained Equations (MICE)
[https://scikit-learn.org/stable/modules/impute.html](https://scikit-learn.org/stable/modules/impute.html)
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This is because `confint()` behaves differently for univariate and multivariate models in many cases.