Maximum likelihood estimation of the fractional differencing parameter in an ARFIMA model using wavelets
β Scribed by Y.K. Tse; V.V. Anh; Q. Tieng
- Book ID
- 108453337
- Publisher
- Elsevier Science
- Year
- 2002
- Tongue
- English
- Weight
- 49 KB
- Volume
- 59
- Category
- Article
- ISSN
- 0378-4754
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
To obtain the likelihood of a non-Gaussian state-space model, Durbin and Koopman (1997, Biometrika, 84, 669 -684) ΓΏrst calculate the likelihood under an approximating linear Gaussian model and then use Monte Carlo methods to estimate the necessary adjustment factor. We show that Durbin and Koopman's
The asymptotic covariance matrix of the maximum likelihood estimator for the log-linear model is given for a general class of conditional Poisson distributions which include the unconditional Poisson, multinomial and product-multinomial, aa special cases. The general conditions are given under which