Results 71 to 80 of about 204,929 (198)

Uniform Bias Study and Bahadur Representation for Local Polynomial Estimators of the Conditional Quantile Function [PDF]

This paper investigates the bias and the Bahadur representation of a local polynomial estimator of the conditional quantile function and its derivatives.
Camille Sabbah, Emmanuel Guerre
core  

Approximation of high quantiles from intermediate quantiles

, 2016
Motivated by applications requiring quantile estimates for very small probabilities of exceedance, this article addresses estimation of high quantiles for probabilities bounded by powers of sample size with exponents below -1.
de Valk, Cees
core   +1 more source

Conditional quantile processes based on series or many regressors [PDF]

Quantile regression (QR) is a principal regression method for analyzing the impact of covariates on outcomes. The impact is described by the conditional quantile function and its functionals. In this paper we develop the nonparametric QR series framework,
Alexandre Belloni, Ivan Fernandez-Val, Victor Chernozhukov   +2 more
core  

An R Implementation of the Polya-Aeppli Distribution [PDF]

, 2014
An efficient implementation of the Polya-Aeppli, or geometirc compound Poisson, distribution in the statistical programming language R is presented.
Burden, Conrad J.
core  

Quantile‐locating functions and the distance between the mean and quantiles

Statistica Neerlandica, 1993
Given a random variable X with finite mean, for each 0 < p < 1, a new sharp bound is found on the distance between a p‐quantile of X and its mean in terms of the central absolute first moment of X. The new bounds strengthen the fact that the mean of X is within one standard deviation of any of its medians, as well as a recent quantile ...
Gilat, D., Hill, Theodore P.
openaire   +3 more sources

Parametric Modeling of Quantile Regression Coefficient Functions

Biometrics, 2015
SummaryEstimating the conditional quantiles of outcome variables of interest is frequent in many research areas, and quantile regression is foremost among the utilized methods. The coefficients of a quantile regression model depend on the order of the quantile being estimated.
Frumento P, Bottai M
openaire   +4 more sources

Nonparametric Estimation of Quantile-Based Mean Inactivity Time Function

Statistica
In this article, we propose non-parametric estimators for mean inactivity time function for complete and censored data. The asymptotic properties of the estimators are established using suitable regularity conditions.
Ivallappil Chenichery Aswin, Paduthol Godan Sankaran, Sreenarayanapurath Madhavan Sunoj   +2 more
doaj   +1 more source

Quantile Approximation of the Chi–square Distribution using the Quantile Mechanics [PDF]

, 2017
In the field of probability and statistics, the quantile function and the quantile density function which is the derivative of the quantile function are one of the important ways of characterizing probability distributions and as well, can serve as a
Adamu, M. O., Anake, T. A., Okagbue, H. I.   +2 more
core  

Posterior Probabilities of Dominance for Wealth Distributions

Econometrics
Probability distributions, which are typically used to describe income distributions, are not suitable to describe a population’s distribution of wealth because of the existence of negative observations and a large concentration of values close to zero ...
William Griffiths, Duangkamon Chotikapanich   +1 more
doaj   +1 more source

Enhancing ultra-short-term wind power forecasting using the Copula quantile regression method

工程科学学报
In recent years, the shift toward renewable energy in China’s power industry has been remarkable, with the installed capacity of renewables surpassing that of coal-fired power.
Junhong GUO, Xiaoxuan WANG, Yuexin WANG, Wei LI, Yi DING, Hongtao JIA   +5 more
doaj   +1 more source