Results 121 to 130 of about 3,632 (159)

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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Simulation-assisted saddlepoint approximation

Journal of Statistical Computation and Simulation, 2008
A general saddlepoint/Monte Carlo method to approximate (conditional) multivariate probabilities is presented. This method requires a tractable joint moment generating function (m.g.f.), but does not require a tractable distribution or density. The method is easy to program and has a third-order accuracy with respect to increasing sample size in ...
R. W. Butler, R. K. Sutton, J. G. Booth, P. Ohman Strickland   +3 more
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Inverting a saddlepoint approximation

Statistics & Probability Letters, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Modified Branching Process and Saddlepoint Approximations

Lobachevskii Journal of Mathematics, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Saddlepoint approximations for estimating equations

Biometrika, 1983
Let X be a random variable (or a random vector) with probability density f(x,\(\theta)\). The function \(\Psi (x,\theta)\) is assumed to be monotonically decreasing in \(\theta\) for all x and \(E\Psi(X,\theta)=0\) for all \(\theta\). Given a random sample \(x_ 1,...,x_ n\) from such a distribution, an estimate of \(\theta\) is provided by the unique ...
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Saddlepoint Approximations

1995
Abstract Although introduced more than 60 years ago it is only during the last 15 years that there has been a systematic development of saddlepoint approximations. These approximations give a highly accurate expression for the tail of a distribution, not only in the centre of the distribution but also for very small tail probabilities ...
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Uniform saddlepoint approximations

Advances in Applied Probability, 1988
The validity of the saddlepoint expansion evaluated at the pointyis considered in the limitytending to ∞. This is done for the expansions of the density and of the tail probability of the meanofni.i.d. random variables and also for the expansion of the tail probability of a compound Poisson sum, whereNis a Poisson random variable.
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Saddlepoint Approximations for Regression Models

Biometrika, 1991
SUMMARY This paper uses the techniques of saddlepoint or tilted-exponential approximation to develop an approximation to the small-sample distribution of estimators defined by a system of estimating equations when observations are independently but not identically distributed. This allows for the explicit treatment of models with explanatory variables.
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On the empirical saddlepoint approximation

Biometrika, 1989
Summary: The properties of the saddlepoint approximation are investigated when the required cumulant generating function is obtained empirically. Properties of the empirical moment generating function and empirical cumulant generating function and derivatives of these processes which are needed for this study are derived first, in particular their ...
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Extended Saddlepoint Approximation Methods

2018
In the previous chapter, we assume that the cumulant generating function (cgf) of the underlying random variable X is known in closed form. The saddlepoint equation involves the first order derivative of the cgf and one can solve for the saddlepoint by a root finding algorithm.
Yue Kuen Kwok, Wendong Zheng
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