Results 91 to 100 of about 204,929 (198)

A quantile approach to the box-cox transformation in random samples. [PDF]

This paper presents an alternative approach to the likelihood methods for estimating the parameter A in the Box-Cox family of transformations when the data arise from a random sample.
Velilla, Santiago
core  

Comparing Estimation Methods for the Power–Pareto Distribution

Econometrics
Non-negative distributions are important tools in various fields. Given the importance of achieving a good fit, the literature offers hundreds of different models, from the very simple to the highly flexible.
Frederico Caeiro, Mina Norouzirad
doaj   +1 more source

A Note on Implementing Box-Cox Quantile Regression [PDF]

The Box-Cox quantile regression model using the two stage method suggested by Chamberlain (1994) and Buchinsky (1995) provides a flexible and numerically attractive extension of linear quantile regression techniques.
Fitzenberger, Bernd, Wilke, Ralf A., Zhang, Xuan   +2 more
core  

Consistent scoring functions for quantiles

, 2013
A scoring function is consistent for the $\alpha$-quantile functional if, and only if, it is generalized piecewise linear (GPL) of order $\alpha$, up to equivalence. Expressed differently, loss functions that yield quantiles as Bayes rules are GPL functions.
Grant, Kyrill, Gneiting, Tilmann
openaire   +2 more sources

Quantile Function on Scalar Regression Analysis for Distributional Data. [PDF]

J Am Stat Assoc, 2020
Yang H, Baladandayuthapani V, Rao AUK, Morris JS.   +3 more
europepmc   +1 more source

Reconditioning your quantile function

, 2017
Monte Carlo simulation is an important tool for modeling highly nonlinear systems (like particle colliders and cellular membranes), and random, floating-point numbers are their fuel. These random samples are frequently generated via the inversion method, which harnesses the mapping of the quantile function Q(u) (e.g.
openaire   +2 more sources

Penalized function-on-function linear quantile regression

Computational Statistics
We introduce a novel function-on-function linear quantile regression model to characterize the entire conditional distribution of a functional response for a given functional predictor. Tensor cubic $B$-splines expansion is used to represent the regression parameter functions, where a derivative-free optimization algorithm is used to obtain the ...
Ufuk Beyaztas, Han Lin Shang, Semanur Saricam   +2 more
openaire   +2 more sources

Statistical Analysis of the Induced Ailamujia Lifetime Distribution with Engineering and Bidomedical Applications

Mathematics
Accurate modeling of industrial and biomedical data is often challenging due to skewness, heavy tails, and complex variability, which traditional probability distributions fail to capture.
Mahmoud M. Abdelwahab, Dina A. Ramadan, Sunil Kumar, Mustafa M. Hasaballah, Ahmed Mohamed El Gazar   +4 more
doaj   +1 more source

The Unit Arcsine–Exponential Distribution and Its Statistical Properties with Inference and Application to Reliability Data

Axioms
This paper presents a new continuous data model, the Unit Arcsine–Exponential distribution (UASED), a flexible data model on the unit interval. It is built up by an exponential-based arcsine-type transformation to allow it to represent a very wide range ...
Asmaa S. Al-Moisheer, Khalaf S. Sultan, Moustafa N. Mousa, Mahmoud M. M. Mansour   +3 more
doaj   +1 more source

Returns to Scale of Production Function: Pooled, Within and Between Quantile Regression Approach [PDF]

Production function, Pooled, Between and Within Quantile Regression, Panel data, Production Economics, Research Methods/ Statistical Methods,
Mishra, Ashok K., Reimbaeva, Maya, Shaik, Saleem   +2 more
core   +1 more source