On the Use of Saddlepoint Approximations in High Dimensional Inference

Jens Ledet Jensen ()
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Jens Ledet Jensen: Aarhus University

Sankhya A: The Indian Journal of Statistics, 2021, vol. 83, issue 1, No 15, 379-392

Abstract: Abstract Inference in high dimensional parameter space poses many challenges. One of these is the possible use of saddlepoint approximations. Motivated by a recent use of the saddlepoint approximation to construct a conditional test, we argue that the precision is questionable. We illustrate this by an example giving a 50% relative error in the calculation of the p-value. A power study of the underlying test reveals a low power in many situations. As an alternative it is suggested to use the likelihood ratio test.

Keywords: Conditional test; Higher order asymptotics; Likelihood ratio test; Power; Primary 62F; Secondary 62F03; 62F05 (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s13171-019-00188-x

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