{ "_id": "6a1ee0f4b401979e734108e8", "Package": "STCCGEV", "Title": "Conditional Copula Model for Crop Yield Forecasting", "Version": "1.0.0", "Authors@R": "c(\nperson(\"Marie\", \"Michaelides\", email= \"marie.michaelides@concordia.ca\", role = c(\"aut\")),\nperson(\"Mélina\", \"Mailhot\", email= \"melina.mailhot@concordia.ca\", role = c(\"aut\")),\nperson(\"Yongkun\", \"Li\", email= \"yongkun.li@concordia.ca\", role = c(\"aut\", \"cre\"))\n)", "Description": "Provides functions to model and forecast crop yields using\na spatial temporal conditional copula approach. The package\nincorporates extreme weather covariates and Bayesian Structural\nTime Series models to analyze crop yield dependencies across\nmultiple regions. Includes tools for fitting, simulating, and\nvisualizing results. This method build upon established R\npackages, including 'Hofert' 'et' 'al'. 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