Results 131 to 140 of about 3,632 (159)

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 ...
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Saddlepoint approximation of CreditRisk+

Journal of Banking & Finance, 2002
Abstract CreditRisk+ is an influential and widely implemented model of portfolio credit risk. As a close variant of models long used for insurance risk, it retains the analytical tractability for which the insurance models were designed. Value-at-risk (VaR) can be obtained via a recurrence-rule algorithm, so Monte Carlo simulation can be avoided ...
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Saddlepoint Approximation for Credit Portfolios

2018
We consider a portfolio of loans or bonds, where the loan borrowers or bond issuers may fail to meet the promised cashflows as stated in the loan contracts or bond indentures. These payment defaults lead to credit losses to the holder of the portfolio of these credit instruments or names (loans or bonds).
Yue Kuen Kwok, Wendong Zheng
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Saddlepoint approximations for subordinator processes

Journal of Statistical Computation and Simulation, 2015
ABSTRACTWe develop the saddlepoint approximations in obtaining the transition functions for general subordinator processes. We derive explicit expressions of the first- and second-order approximations. Specifically, we consider some particular classes of subordinators including the Poisson processes, the Gamma processes, the α-stable subordinators, and
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Saddlepoint Approximations with Applications

2007
Modern statistical methods use complex, sophisticated models that can lead to intractable computations. Saddlepoint approximations can be the answer. Written from the user's point of view, this book explains in clear language how such approximate probability computations are made, taking readers from the very beginnings to current applications.
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Saddlepoint approximations for bivariate distributions

Journal of Applied Probability, 1990
A saddlepoint approximation is derived for the cumulative distribution function of the sample mean of n independent bivariate random vectors. The derivations use Lugannani and Rice's saddlepoint formula and the standard bivariated normal distribution function. The separate versions of the approximation for the discrete cases are also given.
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Saddlepoint approximations in conditional inference

Journal of Applied Probability, 1993
Saddlepoint approximations are derived for the conditional cumulative distribution function and density ofwhereis the sample mean ofni.i.d. bivariate random variables andg(x, y) is a non-linear function. The relative error of orderO(n–1) is retained.
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Saddlepoint approximations for expectations

2009
Electrical Engineering, Mathematics and Computer ...
Huang, X. (author), Oosterlee, C.W. (author)   +1 more
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Improved Methods of Hazard Rate Function Calculation Using Saddlepoint Approximations

Lobachevskii Journal of Mathematics, 2021
Alya Al Mutairi
exaly  

Saddlepoint Approximations to the CDF of Some Statistics with Nonnormal Limit Distributions

Journal of the American Statistical Association, 1993
Andrew Wood, Ronald W Butler
exaly   +2 more sources