Amanote Research
Register
Sign In
Local Composite Quantile Regression Smoothing for Harris Recurrent Markov Processes
SSRN Electronic Journal
doi 10.2139/ssrn.2638837
Full Text
Open PDF
Abstract
Available in
full text
Date
January 1, 2015
Authors
Degui Li
Runze Li
Publisher
Elsevier BV
Related search
Local Composite Quantile Regression Smoothing: An Efficient and Safe Alternative to Local Polynomial Regression
Journal of the Royal Statistical Society. Series B: Statistical Methodology
Uncertainty
Statistics
Probability
Quantile Regression for Recurrent Gap Time Data
Biometrics
Statistics
Genetics
Probability
Molecular Biology
Biochemistry
Applied Mathematics
Microbiology
Immunology
Biological Sciences
Medicine
Agricultural
Forecasting Economic Variables Using Markov Quantile Regression Approach
On Nummelin Splitting for Continuous Time Harris Recurrent Markov Processes and Application to Kernel Estimation for Multi-Dimensional Diffusions
Stochastic Processes and their Applications
Modeling
Applied Mathematics
Statistics
Probability
Simulation
Quantile Smoothing Splines
Biometrika
Statistics
Probability
Uncertainty
Applied Mathematics
Biological Sciences
Agricultural
Mathematics
Quantile Smoothing Splines
Biometrika
Statistics
Probability
Uncertainty
Applied Mathematics
Biological Sciences
Agricultural
Mathematics
The Local Bootstrap for Markov Processes
Journal of Statistical Planning and Inference
Uncertainty
Applied Mathematics
Statistics
Probability
Wild Bootstrap for Quantile Regression
Biometrika
Statistics
Probability
Uncertainty
Applied Mathematics
Biological Sciences
Agricultural
Mathematics
Bayesian Quantile Regression
SSRN Electronic Journal
