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MPoL-dev / MPoL

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Bayesian Inference (posterior exploration) with MPoL and parametric models

iancze
iancze commented Apr 24, 2021

Is your feature request related to a problem or opportunity? Please describe.
The MPoL framework allows the rapid calculation of gradients w.r.t. model parameters. If the sky-plane model is specified parametrically (i.e., as a sky-plane Gaussian, or Gaussian ring, etc...) and is reasonably low-dimensional (< 100) then the posterior distribution of those parameters can be explored using techni

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enhancement good first issue roadmap

elgabbas / Conservation-Prioritisation-Sensitivity

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R code used for the analyses of the paper: Spatial conservation prioritisation in data-poor countries: a quantitative sensitivity analysis using different taxa

r maxent connectivity species-distribution-modelling zonation protected-areas egypt mammals iucn-red-list reptiles butterflies data-poor sampling-bias surrogates elastic-net-regression quantitative-sensitivity-analysis spatial-conservation-planning spatial-conservation-prioritisation
  • Updated Nov 9, 2020
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