搜索结果: 1-15 共查到“统计学 quantile”相关记录22条 . 查询时间(0.031 秒)
We prove an almost sure weak limit theorem for simple linear rank statistics for samples with continuous distributions functions. As a corollary the result extends to samples with ties, and the vector...
Quantile Regression for Large-scale Applications
Quantile Regression Large-scale Applications
2013/6/14
Quantile regression is a method to estimate the quantiles of the conditional distribution of a response variable, and as such it permits a much more accurate portrayal of the relationship between the ...
Quantile Models with Endogeneity
identification treatment effects structural models instrumental variables
2013/4/28
In this article, we review quantile models with endogeneity. We focus on models that achieve identification through the use of instrumental variables and discuss conditions under which partial and poi...
Adaptive quantile estimation in deconvolution with unknown error distribution
Deconvolution Quantile and distribution function Adaptive es-timation Minimax convergence rates Random Fourier multiplier
2013/4/27
We study the problem of quantile estimation in deconvolution with ordinary smooth error distributions. In particular, we focus on the more realistic setup of unknown error distributions. We develop a ...
Quantile-based classifiers
median-based classifier high-dimensional data misclassification rate skewness
2013/4/27
Quantile classifiers for potentially high-dimensional data are defined by classifying an observation according to a sum of appropriately weighted component-wise distances of the components of the obse...
Quantile correlations and quantile autoregressive modeling
Autocorrelation function Box-Jenkins method Quantile correlation Quantile partial correlation Quantile autoregressive model
2012/11/23
In this paper, we propose two important measures, quantile correlation (QCOR) and quantile partial correlation (QPCOR). We then apply them to quantile autoregressive (QAR) models, and introduce two va...
Asymptotics for penalized spline estimators in quantile regression
Asymptotic normality, B-spline,Penalized spline,Quantile regression
2012/11/22
Quantile regression predicts the $\tau$-quantile of the conditional distribution of a response variable given the explanatory variable for $\tau\in(0,1)$. The aim of this paper is to establish the asy...
Local Quantile Regression
local MLE excess bound propagation condition adaptive bandwidth selection.
2012/9/18
Quantile regression is a technique to estimate conditional quantile curves. It pro-vides a comprehensive picture of a response contingent on explanatory variables. In a exible modeling framework, a sp...
Censored quantile regression processes under dependence and penalization
quantile regression Bahadur representation variable selection weak convergence censored data dependent data
2012/9/18
We consider quantile regression processes from censored data under dependent data structures and derive a uniform Bahadur representation for those processes. We also consider cases where the dimension...
Uniform bias study and Bahadur representation for local polynomial estimators of the conditional quantile function
Bahadur representation Conditional quantile function Local polynomial estimation Econometrics of Auctions
2011/6/20
This paper investigates the bias and the weak Bahadur representation of a local
polynomial estimator of the conditional quantile function and its derivatives.
The bias and Bahadur remainder term are...
Quantile calculus and censored regression
Differential equation estimating integral equation quantile equality fraction regression quantile
2010/10/14
Quantile regression has been advocated in survival analysis to assess evolving covariate effects. However, challenges arise when the censoring time is not always observed and may be covariate-depende...
Quantile estimation with adaptive importance sampling
Quantile estimation law of iterated logarithm adaptive im-portance sampling stochastic approximation Robbins–Monro
2010/3/11
We introduce new quantile estimators with adaptive importance
sampling. The adaptive estimators are based on weighted samples
that are neither independent nor identically distributed. Using a
new l...
A New Approximation to the Normal Distribution Quantile Function
New Approximation Normal Distribution Quantile Function
2010/3/10
We present a new approximation to the normal distribution quan-
tile function. It has a similar form to the approximation of Beasley
and Springer [3], providing a maximum absolute error of less than...
Robust quantile estimation and prediction for spatial processes
Spatial processes Kernel estimate Conditional quantile Spatial prediction
2010/3/9
In this paper, we present a statistical framework for modeling conditional quantiles of spatial processes
assumed to be strongly mixing in space. We establish the L1 consistency and the asymptotic no...
A Quantitative Study of Quantile Based Direct Prior Elicitation from Expert Opinion
location parameter prior elicitation quantile scale parameter shape parameter skewness Taylor expansion
2009/9/22
Eliciting priors from expert opinion enjoys more efficiency and re-
liability by avoiding the statistician potential subjectivity. Since elicitation on
the predictive prior probability space require...