Estimação e previsão no processo INARCH(2)
In the last decades the study of integer-valued time series has gained notoriety due to its broad applicability (modeling the number of car accidents in a given highway, or the number of people infected by a virus are two examples). One of the main interests of this area of study is to make forec...
Na minha lista:
| Autor principal: | |
|---|---|
| Outros Autores: | |
| Formato: | Dissertação |
| Idioma: | por |
| Publicado em: |
Universidade Federal do Rio Grande do Norte
|
| Assuntos: | |
| Endereço do item: | https://repositorio.ufrn.br/jspui/handle/123456789/20963 |
| Tags: |
Adicionar Tag
Sem tags, seja o primeiro a adicionar uma tag!
|
| Resumo: | In the last decades the study of integer-valued time series has gained notoriety due
to its broad applicability (modeling the number of car accidents in a given highway,
or the number of people infected by a virus are two examples). One of the main interests
of this area of study is to make forecasts, and for this reason it is very important
to propose methods to make such forecasts, which consist of nonnegative integer values,
due to the discrete nature of the data. In this work, we focus on the study and
proposal of forecasts one, two and h steps ahead for integer-valued second-order autoregressive
conditional heteroskedasticity processes [INARCH (2)], and in determining
some theoretical properties of this model, such as the ordinary moments of its marginal
distribution and the asymptotic distribution of its conditional least squares estimators.
In addition, we study, via Monte Carlo simulation, the behavior of the estimators for
the parameters of INARCH(2) processes obtained using three di erent methods (Yule-
Walker, conditional least squares, and conditional maximum likelihood), in terms of
mean squared error, mean absolute error and bias. We present some forecast proposals
for INARCH(2) processes, which are compared again via Monte Carlo simulation. As
an application of this proposed theory, we model a dataset related to the number of live
male births of mothers living at Riachuelo city, in the state of Rio Grande do Norte,
Brazil. |
|---|