Normed likelihood as saddlepoint approximation
Journal of Multivariate Analysis, 1988 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Foreword to the Special Issue on Mathematical Methods in Reliability (MMR23)
Applied Stochastic Models in Business and Industry, Volume 40, Issue 5, Page 1206-1208, September/October 2024.
Félix Belzunce, Jorge Navarro
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Empirical Saddlepoint Approximations for Multivariate M-Estimators
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1994 SUMMARY In this paper, we investigate the use of the empirical distribution function in place of the underlying distribution function F to construct an empirical saddlepoint approximation to the density fn of a general multivariate M-estimator.
Ronchetti, Elvezio, Welsh, Alan H.
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Maximum Likelihood and Gaussian Estimation of Continuous Time Models in Finance [PDF]
This paper overviews maximum likelihood and Gaussian methods of estimating continuous time models used in finance. Since the exact likelihood can be constructed only in special cases, much attention has been devoted to the development of methods designed
Jun Yu, Peter C. B. Phillips
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Saddlepoint Approximations for Optimal Unit Root Tests [PDF]
This paper provides a (saddlepoint) tail probability approximation for the distribution of an optimal unit root test. Under restrictive assumptions, Gaussianity and known covariance structure, the order of error of the approximation is given.
Patrick Marsh
core
Polynomially Adjusted Saddlepoint Density Approximations
International Journal of Statistics and Probability, 2014 Improved density approximations are obtained by applying certain moment based polynomial adjustments to the saddlepoint approximation. The proposed technique relies on the saddlepoint approximation to the distribution function of a continuous random variable as well. Additionally, a hybrid density estimate is being introduced.
Serge B. Provost, Susan Z. Sheng
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Saddlepoint approximations as smoothers [PDF]
, 2017 This note investigates the sense in which saddlepoint approximations act as smoothers of discrete distributions. The discrete problem is embedded in a continuous model that closely matches it on the discrete sample space, with saddlepoint approximation ...
Davison, A. C., Wang, Suojin
core
A new approach for approximating the p-value of a class of bivariate sign tests. [PDF]
Sci Rep, 2023 Shanan IAA +2 more
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A Modified Multiplicative Thinning-Based INARCH Model: Properties, Saddlepoint Maximum Likelihood Estimation, and Application. [PDF]
Entropy (Basel), 2023 Xu Y, Li Q, Zhu F.
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Leveraging the genetic correlation between traits improves the detection of epistasis in genome-wide association studies. [PDF]
G3 (Bethesda), 2023 Stamp J +3 more
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