Results 91 to 100 of about 483 (131)
Maximum Likelihood and Gaussian Estimation of Continuous Time Models in Finance
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
core
A Comparison of Saddlepoint Approximations for Marginal Distributions
We discuss some recent (nonparametric) approximations of tail probabilities of marginal distributions. They are based on saddlepoint techniques and have an error of order n-1.
Elvezio Ronchetti
core
Saddlepoint Approximations with Applications
Journal of the Royal Statistical Society Series A: Statistics in Society, 2008 openaire +1 more source
Saddlepoint approximations for expectations
, 2011 X. Huang, C.W. Oosterlee (Kees)
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SADDLEPOINT AND ESTIMATED SADDLEPOINT APPROXIMATIONS FOR OPTIMAL UNIT ROOT TESTS
Econometric Theory, 2011 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. More generally, when innovations are a linear process in martingale differences, the estimated saddlepoint is ...
Patrick Marsh
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Implementation of saddlepoint approximations in resampling problems
Statistics and Computing, 1999 In many situations saddlepoint approximations can replace the Monte Carlo simulation typically used to find the bootstrap distribution of a statistic. We explain how bootstrap and permutation distributions can be expressed as conditional distributions and how methods for linear programming and for fitting generalized linear models can be used to find ...
Angelo J. Canty, Anthony C. Davison
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Partial Saddlepoint Approximations for Transformed Means
Scandinavian Journal of Statistics, 2002 The full saddlepoint approximation for real valued smooth functions of means requires the existence of the joint cumulant generating function for the entire vector of random variables which are being transformed. We propose a mixed saddlepoint‐Edgeworth approximation requiring the existence of a cumulant generating function for only part of the random ...
Jing, Bing Yi, Kolassa, JE, Robinson, J.
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, 2015 The saddlepoint method provides accurate approximations for the distributions of many test statistics, estimators and for important probabilities arising in various stochastic models. The saddlepoint approximation is a large deviations technique which is
Gatto, Riccardo, Riccardo Gatto
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Saddlepoint approximations to the trimmed mean
Bernoulli, 2004 Saddlepoint approximations for the trimmed mean and the studentized trimmed mean are established. Some numerical evidence on the quality of our saddlepoint approximations is also included.
Bing-Yi Jing, Gengsheng Qin
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Uniformity of Double Saddlepoint Conditional Probability Approximations
Journal of Multivariate Analysis, 1998 This paper presents results showing that the error involved in using the double saddlepoint distribution function approximations of Skovgaard (1987,J. Appl. Probab.24875–887) are uniformly bounded.
John E Kolassa
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