Zobrazeno 1 - 10
of 163
pro vyhledávání: '"62e99"'
Autor:
Park, Jihyun, Sarantsev, Andrey
We model time series of VIX (monthly average) and monthly stock index returns. We use log-Heston model: logarithm of VIX is modeled as an autoregression of order 1. Our main insight is that normalizing monthly stock index returns (dividing them by VI
Externí odkaz:
http://arxiv.org/abs/2410.22471
Autor:
Kosmidis, Ioannis, Zeileis, Achim
We introduce the XBX regression model, a continuous mixture of extended-support beta regressions for modeling bounded responses with or without boundary observations. The core building block of the new model is the extended-support beta distribution,
Externí odkaz:
http://arxiv.org/abs/2409.07233
Measuring the concentration of random variables is a fundamental concept in probability and statistics. Here, we explore a type of concentration measure for continuous random variables with bounded support and use it to provide a notion of stochastic
Externí odkaz:
http://arxiv.org/abs/2406.02894
Autor:
Acero, William, Molina, Isabel
When estimating area means, direct estimators based on area-specific data, are usually consistent under the sampling design without model assumptions. However, they are inefficient if the area sample size is small. In small area estimation, model ass
Externí odkaz:
http://arxiv.org/abs/2403.15384
This paper presents a new methodology for generating continuous statistical distributions, integrating the exponentiated odds ratio within the framework of survival analysis. This new method enhances the flexibility and adaptability of distribution m
Externí odkaz:
http://arxiv.org/abs/2402.17294
Publikováno v:
Statist. Surv. 18, 163 - 298, 2024
Quantifying the similarity between datasets has widespread applications in statistics and machine learning. The performance of a predictive model on novel datasets, referred to as generalizability, depends on how similar the training and evaluation d
Externí odkaz:
http://arxiv.org/abs/2312.04078
Autor:
Sparkes, Shane, Zhang, Lu
A classical problem of statistical inference is the valid specification of a model that can account for the statistical dependencies between observations when the true structure is dense, intractable, or unknown. To address this problem, a new varian
Externí odkaz:
http://arxiv.org/abs/2310.11554
Autor:
Marcy, Peter W., Morrison, Rebecca E.
Over the last decade, a series of applied mathematics papers have explored a type of inverse problem--called by a variety of names including "inverse sensitivity", "pushforward based inference", "consistent Bayesian inference", or "data-consistent in
Externí odkaz:
http://arxiv.org/abs/2211.15730
Autor:
Konen, Dimitri
We show that in any Euclidean space, an arbitrary probability measure can be reconstructed explicitly by its geometric (or spatial) distribution function. The reconstruction takes the form of a (potentially fractional) linear PDE, where the different
Externí odkaz:
http://arxiv.org/abs/2208.11551
Gau\ss (1823) proved a sharp upper bound on the probability that a random variable falls outside a symmetric interval around zero when its distribution is unimodal with mode at zero. For the class of all distributions with mean at zero, Bienaym\'e (1
Externí odkaz:
http://arxiv.org/abs/2208.08813