Quantile
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Most downloaded papers in Quantile
A re lone inventors more or less likely to invent breakthroughs? Recent research has attempted to resolve this question by considering the variance of creative outcome distributions. It has implicitly assumed a symmetric thickening or... more
Are lone inventors more or less likely to invent breakthroughs? Recent research has attempted to resolve this question by considering the variance of creative outcome distributions. It has implicitly assumed a symmetric thickening or... more
In this paper we assess accuracy of some commonly used estimators of upper quantiles of a right skewed distribution under both parameter and model uncertainty. In particular, for each of lognormal, log-logistic, and log-double exponential... more
A method to estimate an extreme quantile that requires no distributional assumptions is presented. The approach is based on transformed kernel estimation of the cumulative distribution function (cdf). The proposed method consists of a... more
This paper applies quantile data analysis to input modeling in simulation. We introduce the use of QIQ plots to identify suitable distributions fitting the data and comparison distribution PP plots to test the fit. Two examples illustrate... more
A re lone inventors more or less likely to invent breakthroughs? Recent research has attempted to resolve this question by considering the variance of creative outcome distributions. It has implicitly assumed a symmetric thickening or... more
Quantile regression is applied in two retail credit risk assessment exercises exemplifying the power of the technique to account for the diverse distributions that arise in the financial service industry. The first application is to... more
Some of the most powerful techniques currently available to test the goodness of fit of a hypothesized continuous cumulative distribution function (CDF) use statistics based on the empirical distribution function (EDF), such as those of... more
The generalized Pareto distribution is a two-parameter distribution that contains uniform, exponential, and Pareto distributions as special cases. It has applications in a number of fields, including reliability studies and the analysis... more
We discuss the asymptotic validity of confidence intervals for quantiles of performance variables when simulating a Markov chain. We show that a batch quantile methodology (similar to the batch means method) can be applied to obtain... more
A quantile regression model for counts of breeding Cape Sable seaside sparrows Ammodramus maritimus mirabilis (L.) as a function of water depth and previous year abundance was developed based on extensive surveys, 1992-2005, in the... more
In order to estimate the effective dose such as the 0.5 quantile ED 50 in a bioassay problem various parametric and semiparametric models have been used in the literature. If the true dose-response curve deviates significantly from the... more
Investigating the factors affecting CO2 emissions has always been a challenge. One problem with existing studies is that these studies have been relied on mean-based regression approaches, such as ordinary least squares (OLS) or... more
The problem of missing values commonly arises in data sets, and imputation is usually employed to compensate for non-response. We propose a novel imputation method based on quantiles, which can be implemented with or without the presence... more
The purpose of this paper is to provide a strategic collaborative approach to risk and quality control in a cooperative supply chain by using a Neyman-Pearson quantile risk framework for the statistical control of risks. The paper is... more
Many processes can be represented in a simple form as infinite-order linear series. In such cases, an approximate model is often derived as a truncation of the infinite-order process, for estimation on the finite sample. The literature... more
We propose a new regression method to estimate the impact of explanatory variables on quantiles of the unconditional (marginal) distribution of an outcome variable. The proposed method consists of running a regression of the (recentered)... more
We introduce a general approach to nonlinear quantile regression modelling that is based on the specification of the copula function that defines the dependency structure between the variables of interest. Hence we extend Koenker and... more
Often, in industrial stress testing, meteorological data analysis, athletic events, and other similar situations, measurements may be made sequentially and only values larger or smaller than all previous ones are observed. When the number... more
Sample selection problems are pervasive when working with micro economic models and datasets of individuals, households or firms. During the last three decades, there have been very significant developments in this area of econometrics.... more
A new approach is presented here to better take into account inter-individual growth variability in age-structured models used for stock assessment. Cohort analysis requires knowledge of the age structure of the catch, generally derived... more
Aim Understanding the processes that drive invasion success of alien species has received considerable attention in current ecological research. From an evolutionary point of view, many studies have shown that the phylogenetic similarity... more
Primary production must constrain the amount of fish and invertebrates available to expanding fisheries; however the degree of limitation has only been demonstrated at regional scales to date.
Using the concept of near-exact approximation to a distribution we developed two different near-exact approximations to the distribution of the product of an odd number of particular independent Beta random variables (r.v.'s). One of them... more
Many processes can be represented in a simple form as infinite-order linear series. In such cases, an approximate model is often derived as a truncation of the infinite-order process, for estimation on the finite sample. The literature... more