The aim of this article is to construct spatial models for the activation of sweat glands for healthy subjects and subjects suffering from peripheral neuropathy by using videos of sweating recorded from the subjects. The sweat patterns are regarded as realizations of spatial point processes and two point process models for the sweat gland activation and two methods for inference are proposed. Several image analysis steps are needed to extract the point patterns from the videos and some incorrectly identified sweat gland locations may be present in the data. To take into account the errors, we either include an error term in the point process model or use an estimation procedure that is robust with respect to the errors.
Bibliographical noteFunding Information:
Academy of Finland, 295100; 306875; 32711; Swedish Foundation for Strategic Research, SSF AM13‐0066; Swedish Research Council, VR 2013‐5212 Funding information
Mikko Kuronen and Mari Myllymäki have been financially supported by the Academy of Finland (Project Numbers 295100, 306875, and 327211) and Aila Särkkä by the Swedish Research Council (VR 2013‐5212) and by the Swedish Foundation for Strategic Research (SSF AM13‐0066). The authors thank Matti Vihola for useful discussions. We are also grateful for the two anonymous reviewers for the valuable comments.
© 2021 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd.
- Bayesian inference
- independent thinning
- peripheral neuropathy
- point pattern
- sequential point process
- soft-core inhibition