Abstract
Reactivity ratio estimation was carried out in various nonlinear models using Markov Chain Monte Carlo (MCMC) technique and an error‐in‐variables (EVM) regression model. The implementation steps for three different polymerization case studies are discussed in detail and the results from this work are compared to previously used approximation methods. Approximation techniques that rely on linear regression theory are shown to produce inaccurate joint confidence regions (JCRs). Therefore, in this paper, we explore MCMC techniques that can be used to produce JCRs with correct shape and probability content. In addition, the paper illustrates how an EVM model can be used in tackling any type of regression problem, including multi‐response problems.
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