Results 61 to 70 of about 704,599 (275)
Confidence interval Calculation & Evaluating Markov regime switching Precision for Value-at-Risk Estimation: A Case Study on Tehran Stock Exchange Index (TEDPIX) [PDF]
تحقیقات مالی, 2016 Value at risk is one of the most common risk measures which, considering its dependency on volatility return, uncertainty of volatility prediction models and existing bias in parameter prediction, is subject to bias.
Rasoul Sajjad, Roya Taherifar
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Mathematics, 2022 For a fixed time, t, and a horizon time, b, the probability of default (PD) measures the probability that an obligor, that has paid his/her credit until time t, runs into arrears not later that time t+b.
Rebeca Peláez +2 more
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Bootstraping financial time series [PDF]
, 2002 It is well known that time series of returns are characterized by volatility clustering and excess kurtosis. Therefore, when modelling the dynamic behavior of returns, inference and prediction methods, based on independent and/or Gaussian observations ...
Pascual, Lorenzo, Ruiz Ortega, Esther
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Arthritis Care &Research, Accepted Article.Objectives This study aimed to investigate hand function trajectories over 5 years in primary hand osteoarthritis. Additionally, determinants of baseline and longitudinal hand function were assessed. Methods 538 patients with both baseline and 5‐year study visits were analyzed.
Annemiek V.E.M. Olde Meule +4 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
A fuzzy nonparametric Shewhart chart based on the bootstrap approach
International Journal of Applied Mathematics and Computer Science, 2015 In this paper, we consider a nonparametric Shewhart chart for fuzzy data. We utilize the fuzzy data without transforming them into a real-valued scalar (a representative value).
Wang Dabuxilatu, Hryniewicz Olgierd
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A Weighted Bootstrap Approach to Bootstrap Iteration
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2000 Summary The operation of resampling from a bootstrap resample, encountered in applications of the double bootstrap, maybe viewed as resampling directly from the sample but using probability weights that are proportional to the numbers of times that sample values appear in the resample.
Hall, Peter, Maesono, Y
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Bootstrap confidence sets under model misspecification [PDF]
, 2014 A multiplier bootstrap procedure for construction of likelihood-based confidence sets is considered for finite samples and a possible model misspecification. Theoretical results justify the bootstrap validity for a small or moderate sample size and allow
Spokoiny, Vladimir, Zhilova, Mayya
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Advanced Healthcare Materials, EarlyView.Wound closure is governed by geometry‐orientation coupling: aligned fibers speed migration along their axis but hinder perpendicular advance. In vivo diabetic wound experiments with composition‐matched fibrin, combined with an anisotropic diffusion (biased random‐walk) model, quantify this trade‐off and generate a healing landscape.
Yin‐Yuan Huang +13 more
wiley +1 more source
IEEE AccessProbabilistic forecasting models have been developed over the past years in order to aid in the estimation of the uncertainty of the predictive results. A hybrid, bootstrapping long-short term memory (Boot-LSTM)-based model is proposed in this paper, in ...
Ioannis K. Bazionis +4 more
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