| 作成者 |
|
|
|
| 本文言語 |
|
| 出版者 |
|
|
|
| 発行日 |
|
| 収録物名 |
|
| 巻 |
|
| 号 |
|
| 開始ページ |
|
| 終了ページ |
|
| 出版タイプ |
|
| アクセス権 |
|
| Crossref DOI |
|
| 関連DOI |
|
|
|
| 関連URI |
|
|
|
| 関連情報 |
|
|
|
| 概要 |
For a stationary sequence $ { X_i } $ the Markov assumption $ G_2 $, which is weaker than the Doeblin's condition $ D_0 $, is discussed and is used to estimate nonparametric density and transition den...sity. Under the $ G_2 $-assumptions, the rate of convergence to normality of the estimated density is derived. Similar type of results are also derived for estimating the joint density and the estimated transition density.続きを見る
|
Mendeley出力
