A spatio-temporal approach to estimate patterns of climate change (2019)
- Autor:
- Autor USP: LAURINI, MARCIO POLETTI - FEARP
- Unidade: FEARP
- DOI: 10.1002/env.2542
- Subjects: ECONOMETRIA; CLIMA
- Keywords: Climate econometrics; Laplace approximations; Spatio‐temporal models; Structural time series
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Environmetrics
- ISSN: 1099-095X
- Volume/Número/Paginação/Ano: v. 30, p. e2542, 2019
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: bronze
-
ABNT
LAURINI, Marcio Poletti. A spatio-temporal approach to estimate patterns of climate change. Environmetrics, v. 30, p. e2542, 2019Tradução . . Disponível em: https://doi.org/10.1002/env.2542. Acesso em: 01 maio 2024. -
APA
Laurini, M. P. (2019). A spatio-temporal approach to estimate patterns of climate change. Environmetrics, 30, e2542. doi:10.1002/env.2542 -
NLM
Laurini MP. A spatio-temporal approach to estimate patterns of climate change [Internet]. Environmetrics. 2019 ; 30 e2542.[citado 2024 maio 01 ] Available from: https://doi.org/10.1002/env.2542 -
Vancouver
Laurini MP. A spatio-temporal approach to estimate patterns of climate change [Internet]. Environmetrics. 2019 ; 30 e2542.[citado 2024 maio 01 ] Available from: https://doi.org/10.1002/env.2542 - Data cloning: maximum likelihood estimation of DSGE models
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Informações sobre o DOI: 10.1002/env.2542 (Fonte: oaDOI API)
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