On a partly linear autoregressive model with moving average errors
In this paper, we generalise the partly linear autoregression model considered in the literature by including moving average errors when we want to allow a large dependence to the past observations. The strong ergodicity of the process is derived. A consistent procedure to estimate the parametric an...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2010 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/16546 |
| Acceso en línea: | http://hdl.handle.net/11336/16546 |
| Access Level: | acceso abierto |
| Palabra clave: | Ergodicity Fisher-Consistency Moving Average Errors Partly Linear Autoregression Smoothing Techniques https://purl.org/becyt/ford/1.1 https://purl.org/becyt/ford/1 |
| Sumario: | In this paper, we generalise the partly linear autoregression model considered in the literature by including moving average errors when we want to allow a large dependence to the past observations. The strong ergodicity of the process is derived. A consistent procedure to estimate the parametric and nonparametric components is provided together with a test statistic that allows to check the presence of a moving average component in the model. Also, a Monte Carlo study is carried out to check the performance of the given proposals. |
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