Mean Integrated Squared Error of Nonlinear Wavelet-based Estimators with Long Memory Data
β Scribed by Linyuan Li; Yimin Xiao
- Publisher
- Springer Japan
- Year
- 2006
- Tongue
- English
- Weight
- 268 KB
- Volume
- 59
- Category
- Article
- ISSN
- 0020-3157
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## Abstract In this paper we deal with the prediction theory of longβmemory time series. The purpose is to derive a general theory of the convergence of moments of the nonlinear least squares estimator so as to evaluate the asymptotic prediction mean squared error (PMSE). The asymptotic PMSE of two
Hall and Hart (1990) proved that the mean integrated squared error (MISE) of a marginal kernel density estimator from an infinite moving average process X1, )(2 .... may be decomposed into the sum of MISE of the same kernel estimator for a random sample of the same size and a term proportional to th
In this paper, we consider the integrated square error Jn = { f n (x) -f(x)} 2 d x; where f is the common density function of the independent and identically distributed random vectors X1; : : : ; Xn and f n is the kernel estimator with a data-dependent bandwidth. Using the approach introduced by Ha