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The univariate quantile-quantile (Q-Q) plot is a well-known graphical tool for examining whether two data sets are generated from the same distribution or not. It is also used to determine how well a specified probability distribution fits…

Statistics Theory · Mathematics 2014-07-07 Subhra Sankar Dhar , Biman Chakraborty , Probal Chaudhuri

In this paper we introduce new estimators of the coefficient functions in the varying coefficient regression model. The proposed estimators are obtained by projecting the vector of the full-dimensional kernel-weighted local polynomial…

Statistics Theory · Mathematics 2012-03-05 Young K. Lee , Enno Mammen , Byeong U. Park

A number of fundamental quantities in statistical signal processing and information theory can be expressed as integral functions of two probability density functions. Such quantities are called density functionals as they map density…

Information Theory · Computer Science 2018-02-14 Alan Wisler , Visar Berisha , Andreas Spanias , Alfred O. Hero

We propose a novel machine learning approach for forecasting the distribution of stock returns using a rich set of firm-level and market predictors. Our method combines a two-stage quantile neural network with spline interpolation to…

General Finance · Quantitative Finance 2025-08-05 Jozef Barunik , Martin Hronec , Ondrej Tobek

This paper develops a Bayesian control chart for the percentiles of the Weibull distribution, when both its in-control and out-of-control parameters are unknown. The Bayesian approach enhances parameter estimates for small sample sizes that…

Methodology · Statistics 2013-08-06 Pasquale Erto , Giuliana Pallotta , Christina M. Mastrangelo

This paper focuses on generalizing quantiles from the ordering point of view. We propose the concept of partial quantiles, which are based on a given partial order. We establish that partial quantiles are equivariant under order-preserving…

Statistics Theory · Mathematics 2011-05-31 Alexandre Belloni , Robert L. Winkler

Fractional statistical moments are utilized for various tasks of uncertainty quantification, including the estimation of probability distributions. However, an estimation of fractional statistical moments of costly mathematical models by…

Methodology · Statistics 2024-03-05 Lukáš Novák , Marcos Valdebenito , Matthias Faes

Gaussian functions are commonly used in different fields, many real signals can be modeled into such form. Research aiming to obtain a precise fitting result for these functions is very meaningful. This manuscript intends to introduce a new…

Methodology · Statistics 2021-03-15 Wei Chen

This paper introduces a new three-parameters model called the Weibull-G exponential distribution (WGED) distribution which exhibits bathtub-shaped hazard rate. Some of it's statistical properties are obtained including quantile, moments,…

Statistics Theory · Mathematics 2016-06-24 Abdelfattah Mustafa , B. S. El-Desouky , Shamsan AL-Garash

A multivariate survival function of Weibull Distribution is developed by expanding the theorem by Lu and Bhattacharyya (1990). From the survival function, the probability density function, the cumulative probability function, the…

Statistics Theory · Mathematics 2007-06-13 Cheng K. Lee , Miin-Jye Wen

Estimating percentiles of black-box deterministic functions with random inputs is a challenging task when the number of function evaluations is severely restricted, which is typical for computer experiments. This article proposes two new…

Statistics Theory · Mathematics 2016-05-23 T Labopin-Richard , V Picheny

This paper presents a unified and novel estimation framework for the Weibull, Gamma, and Log-normal distributions based on arbitrary-order moment pairs. Traditional estimation techniques, such as Maximum Likelihood Estimation (MLE) and the…

Methodology · Statistics 2025-05-06 Kang Liu

We develop quantile regression methods for discrete responses by extending Parzen's definition of marginal mid-quantiles. As opposed to existing approaches, which are based on either jittering or latent constructs, we use interpolation and…

Methodology · Statistics 2021-08-25 Marco Geraci , Alessio Farcomeni

For a variant of the algorithm in [Pit19] (arXiv:1903.10816) to compute the approximate density or distribution function of a linear mixture of independent random variables known by a finite sample, it is presented a proof of the functional…

Statistics Theory · Mathematics 2019-06-19 Thomas Pitschel

Varying domains and biased datasets can lead to differences between the training and the target distributions, known as covariate shift. Current approaches for alleviating this often rely on estimating the ratio of training and target…

Machine Learning · Statistics 2020-10-27 Bijan Mazaheri , Siddharth Jain , Jehoshua Bruck

This paper considers the problem of estimating the cumulative distribution function and probability density function of a random variable using data quantized by uniform and non-uniform quantizers. A simple estimator is proposed based on…

Signal Processing · Electrical Eng. & Systems 2018-05-03 Paolo Carbone , Johan Schoukens , István Kollár , Antonio Moschitta

Quantile regression has been successfully used to study heterogeneous and heavy-tailed data. Varying-coefficient models are frequently used to capture changes in the effect of input variables on the response as a function of an index or…

Methodology · Statistics 2021-10-18 Ran Dai , Mladen Kolar

The Weyl-Wigner representation of quantum mechanics allows one to map the density operator in a function in phase space - the Wigner function - which acts like a probability distribution. In the context of statistical mechanics, this…

Quantum Physics · Physics 2023-08-31 Marcos Gil de Oliveira , Alfredo Miguel Ozorio de Almeida

Fertility plans, measured by the number of planned children, have been found to be affected by education and family background via complex tail dependencies. This challenge was previously met with the use of non-parametric jittering…

Methodology · Statistics 2019-11-18 Alina Peluso , Veronica Vinciotti , Keming Yu

The cumulative distribution and quantile functions for the two-sided one sample Kolmogorov-Smirnov probability distributions are used for goodness-of-fit testing. The CDF is notoriously difficult to explicitly describe and to compute, and…

Computation · Statistics 2018-03-02 Paul van Mulbregt
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