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Smoothed weighted empirical likelihood ratio confidence intervals for quantiles
bootstrap doubly censored data empirical likelihood interval censored data partly interval censored data right censored data
2015/12/11
Thus far, likelihood-based interval estimates for quantiles have not been studied in the literature on interval censored case 2 data and partly interval censored data, and, in this context, the use of...
Importance Sampling for Monte Carlo Estimation of Quantiles
quantiles importance sampling large deviations.
2015/7/8
This paper is concerned with applying importance sampling as a variance reduction tool for computing extreme quantiles. A central limit theorem is derived for each of four proposed importance sampling...
Computing Quantiles in Regime-Switching Jump-Diffusions with Application to Optimal Risk Management: a Fourier Transform Approach
regime switching jump-diffusion models Value at Risk risk management Fourier transform methods.
2012/9/14
In this paper we consider the problem of calculating the quantiles of a risky position,the dynamic of which is described as a continuous time regime-switching jump-diffusion, by using Fourier Transfor...
Functional kernel estimators of large conditional quantiles
Conditional quantiles heavy-tailed distributions functional kernel estimator
2011/7/19
We address the estimation of conditional quantiles when the covariate is functional and when the order of the quantiles converges to one as the sample size increases.
Functional kernel estimators of large conditional quantiles
Conditional quantiles heavy-tailed distributions functional kernel estimator extreme-value theory
2011/9/2
Abstract: We address the estimation of conditional quantiles when the covariate is functional and when the order of the quantiles converges to one as the sample size increases. In a first time, we inv...
Estimating conditional quantiles with the help of the pinball loss
nonparametric regression quantile estimation support vector machines
2011/3/21
The so-called pinball loss for estimating conditional quantiles is a well-known tool in both statistics and machine learning. So far, however, only little work has been done to quantify the efficiency...
Estimation of high return period flood quantiles using additional non-systematic information with upper bounded statistical models
return period flood quantiles additional non-systematic information
2010/12/22
This paper proposes the estimation of high return period quantiles using upper bounded distribution functions with Systematic and additional Non-Systematic information. The aim of the developed method...
Flood frequency analysis (FFA) entails the estimation of the upper tail of a probability density function (PDF) of annual peak flows obtained from either the annual maximum series or partial duration ...
Forecasting the Quantiles of Daily Equity Returns Using Realized Volatility: Evidence from the Czech Stock Market
Intraday data heterogeneous autoregressive model
2010/12/6
In this study, we evaluate the quantile forecasts of the daily equity returns on three of the most liquid stocks traded on the Prague Stock Exchange. We follow the recent findings that consider the po...
Multivariate quantiles and multiple-output regression quantiles：From L1 optimization to halfspace depth
Multivariate quantile quantile regression halfspace depth
2010/3/10
A new multivariate concept of quantile, based on a directional
version of Koenker and Bassett’s traditional regression quantiles, is
introduced for multivariate location and multiple-output regressi...
Discussion of “Multivariate quantiles and multiple-output regression quantiles：From L1 optimization to halfspace depth”
Multivariate quantiles multiple-output regression quantiles L1 optimization halfspace depth
2010/3/10
First I would like to congratulate the authors for developing a new concept
of directional quantile contours. The work will contribute well to the pursuit
of multivariate quantiles. The multiple out...
The distribution and quantiles of functionals of weighted empirical distributions when observations have different distributions
Edgeworth-Cornish-Fisher expansions von Mises derivatives Weighted em-pirical distribution
2010/3/10
This paper extends Edgeworth-Cornish-Fisher expansions for the distribution
and quantiles of nonparametric estimates in two ways. Firstly it allows observations to have
different distributions. Seco...
Two approaches to constructing simultaneous confidence bounds for quantiles
Two approaches constructing simultaneous confidence bounds quantiles
2009/9/24
Two approaches to constructing simultaneous confidence bounds for quantiles。
Bahadur's representation of sample quantiles based on smoothed estimates of a distribution function
Bahadur's representation of sample quantiles smoothed estimates of a distribution function
2009/9/24
Bahadur's representation of sample quantiles based on smoothed estimates of a distribution function。
Expansions for Quantiles and Multivariate Moments of Extremes for Distributions of Pareto Type
Bell polynomials Extremes Inversion theorem Moments Pareto Quantiles
2010/3/19
Let Xnr be the rth largest of a random sample of size n from a distribution
F(x) = 1 −P∞i=0 cix− −i for > 0 and > 0. An inversion theorem is proved and used to
derive an expan...