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autoregression

autoregression Autoregression is a time-series forecasting approach that predicts future values from patterns in earlier values of the same measure over time.

Autoregression is a time-series forecasting approach that predicts future values from patterns in earlier values of the same measure over time. In this context, it refers to methods such as neural network autoregression used to estimate future trends or clinical events from past data.

Sources

Drafting source: Cañedo Mayara Carolina; Lopes Thiago Inácio Barros; Rossato Luana; Nunes Isadora Batista; Faccin Izadora Dillis; Salomé Túlio Máximo; Simionatto Simone. Impact of COVID-19 pandemic in the Brazilian maternal mortality ratio: A comparative analysis of Neural Networks Autoregression, Holt-Winters exponential smoothing, and Autoregressive Integrated Moving Average models. 2024; DOI 10.1371/journal.pone.0296064; article XML SHA-256 9242ff8339226865ec50fbd26156c577347b28afb9405a0496bac0676e2fc424. “Impact of COVID-19 pandemic in the Brazilian maternal mortality ratio: A comparative analysis of Neural Networks Autoregression, Holt-Winters exponential smoothing, and Autoregressive Integrated Moving Average models” (10.1371/journal.pone.0296064).
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PsychTerms (psychterms.org), CC BY 4.0, version 2. “autoregression.” Development preview.

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autoregression

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