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Method that improved area selection and consistently enhance forecast skill.

Two statistical models were used to evaluate the seasonal forecasts: Canonical Correlation Analysis (CCA) implemented in CPT, and Multiple Factorial Analysis (MFA), which allows integrating several regions or several predictors simultaneously. Using the results from the teleconnection analysis, fore...

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Main Author: CGIAR Research Program on Climate Change, Agriculture and Food Security
Format: Informe técnico
Language:Inglés
Published: 2017
Subjects:
models
development
selection
rural development
analysis
systems
agrifood systems
correlation
factorial analysis
Online Access:https://hdl.handle.net/10568/123221
Summary:Two statistical models were used to evaluate the seasonal forecasts: Canonical Correlation Analysis (CCA) implemented in CPT, and Multiple Factorial Analysis (MFA), which allows integrating several regions or several predictors simultaneously. Using the results from the teleconnection analysis, forecast skill in Colombia for the period form 1982-2013 was assessed.

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