Results 31 to 40 of about 3,632 (159)
Explaining the Saddlepoint Approximation [PDF]
The American Statistician, 1999 Abstract Saddlepoint approximations are powerful tools for obtaining accurate expressions for densities and distribution functions. We give an elementary motivation and explanation of approximation techniques, starting with Taylor series expansions and progressing to the Laplace approximation of integrals.
Constantino Goutis, George Casella
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Composite Likelihood Inference by Nonparametric Saddlepoint Tests [PDF]
, 2013 The class of composite likelihood functions provides a flexible and powerful toolkit to carry out approximate inference for complex statistical models when the full likelihood is either impossible to specify or unfeasible to compute.
Lunardon, Nicola, Ronchetti, Elvezio
core +4 more sources
Tail Exactness of Multivariate Saddlepoint Approximations [PDF]
Scandinavian Journal of Statistics, 1999 We consider a log‐concave density f in Rm satisfying certain weak conditions, particularly on the Hessian matrix of log f. For such a density, we prove tail exactness of the multivariate saddlepoint approximation. The proof is based on a local limit theorem for the exponential family generated by f.
Barndorff-Nielsen, O. E. +1 more
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Joint Modelling of Gas and Electricity spot prices [PDF]
, 2009 The recent liberalization of the electricity and gas markets has resulted in the growth of energy exchanges and modelling problems. In this paper, we modelize jointly gas and electricity spot prices using a mean-reverting model which fits the ...
Frikha, Noufel, Lemaire, Vincent
core +5 more sources
Saddlepoint approximation for moment generating functions of truncated random variables
, 2005 We consider the problem of approximating the moment generating function (MGF) of a truncated random variable in terms of the MGF of the underlying (i.e., untruncated) random variable.
Butler, Ronald W., Wood, Andrew T. A.
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Efficient simulation of density and probability of large deviations of sum of random vectors using saddle point representations [PDF]
, 2012 We consider the problem of efficient simulation estimation of the density function at the tails, and the probability of large deviations for a sum of independent, identically distributed, light-tailed and non-lattice random vectors.
Ankush Agarwal +8 more
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Health Science Reports, Volume 8, Issue 9, September 2025.ABSTRACT Background and Aims Cause‐specific mortality (CSM) count prediction plays a vital role in the context of public health policy. In this study, we introduce a new analytical approach, which is divided into three phases to answer specific questions regarding CSM due to 14 specific causes by computing different simple, compound, and conditional ...
Aditya Chakraborty, Mohan D. Pant
wiley +1 more source
On the relationship between empirical likelihood and empirical saddlepoint approximation for multivariate M-estimators [PDF]
, 2017 SUMMARY By comparing the expansions of the empirical log-likelihood ratio and the empirical cumulant generating function calculated at the saddlepoint, we investigate the relationship between empirical likelihood and empirical saddlepoint approximations.
MONTI, ANNA CLARA, RONCHETTI, ELVEZIO
core
, 2007 Consider a model parameterized by a scalar parameter of interest and a nuisance parameter vector. Inference about the parameter of interest may be based on the signed root of the likelihood ratio statistic R.
Kolassa, John E., Zhang, Juan
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ON BEHAVIOR OF THE SADDLEPOINT IN THE SADDLEPOINT APPROXIMATIONS [PDF]
Bulletin of informatics and cybernetics, 1999 Summary: In this paper we examine the behavior of the saddlepoint in the saddlepoint approximations for the \(M\)-estimators of location. The results of the study are useful when applying a numerical method to solve an equation with respect to the saddlepoint and when considering the approximations from a theoretical point of view.
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