Climate Foresight: Difference between revisions
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(Created page with "Client: William Jones <william.jones@embecosm.com> Dynamic Causal Modeling is a Bayesian statistical technique for reverse engineering time series data. One of the ongoing challenges in applying such statistical models is how to visualise the multiverse of possible outcomes that the algorithm derives. Your goal is to create an evidence-based visualisation of possible climate futures that allows users to interrogate and compare projections from a complete simplified carb...") |
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Client: William Jones <william.jones@embecosm.com> | Client: William Jones, Embecosm <william.jones@embecosm.com> | ||
Dynamic Causal Modeling is a Bayesian statistical technique for reverse engineering time series data. One of the ongoing challenges in applying such statistical models is how to visualise the multiverse of possible outcomes that the algorithm derives. Your goal is to create an evidence-based visualisation of possible climate futures that allows users to interrogate and compare projections from a complete simplified carbon-climate model within the Dynamic Causal Modeling framework. | Dynamic Causal Modeling is a Bayesian statistical technique for reverse engineering time series data. One of the ongoing challenges in applying such statistical models is how to visualise the multiverse of possible outcomes that the algorithm derives. Your goal is to create an evidence-based visualisation of possible climate futures that allows users to interrogate and compare projections from a complete simplified carbon-climate model within the Dynamic Causal Modeling framework. | ||
Latest revision as of 10:51, 26 October 2023
Client: William Jones, Embecosm <william.jones@embecosm.com>
Dynamic Causal Modeling is a Bayesian statistical technique for reverse engineering time series data. One of the ongoing challenges in applying such statistical models is how to visualise the multiverse of possible outcomes that the algorithm derives. Your goal is to create an evidence-based visualisation of possible climate futures that allows users to interrogate and compare projections from a complete simplified carbon-climate model within the Dynamic Causal Modeling framework.
