Kernel density estimation for linear processes

By Wei Biao Wu, J. Mielniczuk. 2002

57 citations recorded by the source corpus.

Subfields: Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/eac3e8501c1b5e6a6fd5431025cb51ad439e5641

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Finance

1. Wei Biao Wu
2. Xiaofeng Shao
3. Zhou Zhou
4. Weidong Liu
5. István Berkes
6. Andreas Hagemann
7. Siegfried Hormann
8. Xiaohui Chen

In Statistics and Probability

1. Wei Biao Wu
2. Tommaso Cai
3. Andreas Hagemann
4. Xiaohui Chen
5. Xiaofeng Shao
6. Lajos Horv'ath
7. Wenguang Sun
8. Michael Vogt

Citations in the corpus

• On the Bahadur representation of sample quantiles for dependent sequences (2005, background): “od and established a central limit theory for stationary processes; see also [14]. Wu and Woodroofe [37] present some recent developments. Several of its applications on various problems are given in [15, 18, 31, 32, 34]. BAHADUR REPRESENTATION 3 Historically many limit theorems for dependent random”
• M-estimation of linear models with dependent errors (2004, unknown): “i,n θ;Fi−1), Nn(θ) = Xn i=1 {ψ1(−z′ i,nθ;Fi−1)− ϕ(−z ′ i,nθ)}zi,n. (53) The summands of Mn form (triangular array) martingale differences with respect to the filter σ(Fi). A similar argument is used in Wu and Mielniczuk (2002). Since Pn i=1 zi,nz ′ i,n = Idp, we have n−1/2 = O(r n) and by (16), n−2 = ”