Modeling associations between latent event processes governing time series of pulsing hormones.

ABSTRACT: This work is motivated by a desire to quantify relationships between two time series of pulsing hormone concentrations. The locations of pulses are not directly observed and may be considered latent event processes. The latent event processes of pulsing hormones are often associated. It is this joint relationship we model. Current approaches to jointly modeling pulsing hormone data generally assume that a pulse in one hormone is coupled with a pulse in another hormone (one-to-one association). However, pulse coupling is often imperfect. Existing joint models are not flexible enough for imperfect systems. In this article, we develop a more flexible class of pulse association models that incorporate parameters quantifying imperfect pulse associations. We propose a novel use of the Cox proces

SUBMITTER: Liu H 

PROVIDER: S-EPMC6022408 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature