Pages that link to "Item:Q1361684"
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The following pages link to Asymptotically optimal bandwidth selection rules for the kernel density estimator with dependent observations (Q1361684):
Displaying 12 items.
- Density estimation in the \(L^ \infty\) norm for dependent data with applications to the Gibbs sampler (Q688378) (← links)
- Data-driven bandwidth choice for density estimation based on dependent data (Q916260) (← links)
- Neural networks for bandwidth selection in local linear regression of time series (Q1023573) (← links)
- An asymptotically optimal window selection rule for kernel density estimates (Q1080584) (← links)
- A local cross-validation algorithm for dependent data (Q1209931) (← links)
- Asymptotic distribution of bandwidth selectors in kernel regression estimation (Q1324972) (← links)
- A study on bandwidth selection in density estimation under dependence (Q1368842) (← links)
- Moment inequalities for spatial processes (Q2483441) (← links)
- Adaptive sampling schemes for density estimation (Q2498749) (← links)
- A kernel mode estimate under random left truncation and time series model: asymptotic normality (Q2516630) (← links)
- On the estimation of the marginal density of a moving average process (Q2714931) (← links)
- Optimal sampling for density estimation in continuous time (Q4431625) (← links)
