Abstract
This paper establishes a posterior convergence rate theorem for general Markov chains. Our approach is based on the Hausdorff α-entropy introduced by Xing (Electronic Journal of Statistics 2:848–62, 2008) and Xing and Ranneby (Journal of Statistical Planning and Inference 139 (7):2479–89, 2009). As an application we illustrate our results on a non linear autoregressive model.
| Original language | English |
|---|---|
| Pages (from-to) | 5910-5921 |
| Journal | Communications in Statistics - Theory and Methods |
| Volume | 52 |
| Issue number | 16 |
| Early online date | 2021 |
| DOIs | |
| Publication status | Published - 2023 |
Subject classification (UKÄ)
- Probability Theory and Statistics
Free keywords
- 62F15
- 62G07
- 62G20
- Density function
- Hausdorff entropy
- Hellinger metric
- Markov chain
- posterior distribution
- rate of convergence