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On the Use of Saddlepoint Approximations in High Dimensional Inference

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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.

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  1. Department of Mathematics, Aarhus University, Ny Munkegade 118, 8000 Aarhus C, Aarhus, Denmark

    Jens Ledet Jensen

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  1. Jens Ledet Jensen
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Correspondence to Jens Ledet Jensen.

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Jensen, J.L. On the Use of Saddlepoint Approximations in High Dimensional Inference. Sankhya A 83, 379–392 (2021). https://doi.org/10.1007/s13171-019-00188-x

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  • DOI: https://doi.org/10.1007/s13171-019-00188-x

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