Data/hora: 12/06/2024 11:31:47

Provedor de dados: | 31
País: | United States
Título: | REDUCTION OF STATE VARIABLE DIMENSION IN STOCHASTIC DYNAMIC OPTIMIZATION MODELS WHICH USE TIME-SERIES DATA
Autores: | Burt,   Oscar R.; Taylor,   C. Robert.
Data: | 2003-12-24
Ano: | 1989
Palavras-chave: | Research Methods/ Statistical Methods.
Resumo: | Statistical procedures are developed for reducing the number of autonomous state variables in stochastic dynamic optimization models when these variables follow a stationary process over time.  These methods essentially delete part of the information upon which decisions are based while maintaining a logically consistent model.  The relatively simple linear autoregressive process as well as the general case is analyzed and the necessary formulae for practical application are derived.  Several applications in agricultural economics are discussed and results presented which quantify the relative amount of information sacrificed with the reduction in number of state variables.
Tipo: | Journal Article
Idioma: | Inglês

Identificador:

11769

http://purl.umn.edu/32349

Editor: | AgEcon Search
Relação: | Western Journal of Agricultural Economics&gt;Volume 14, Number 02, December 1989

Formato:

10

application/pdf