On the Use of Saddlepoint Approximations in High Dimensional Inference

TY - JOUR

T1 - On the Use of Saddlepoint Approximations in High Dimensional Inference

AU - Jensen, Jens Ledet

PY - 2021/2

Y1 - 2021/2

N2 - 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.

AB - 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.

U2 - 10.1007/s13171-019-00188-x

DO - 10.1007/s13171-019-00188-x

M3 - Journal article

SN - 0976-8378

VL - 83

SP - 379

EP - 392

JO - Sankhya A

JF - Sankhya A

IS - 1

ER -