Rectangular Latent Markov Models for Time-Specific Clustering, with An Analysis of the Wellbeing of Nations
Gordon John Anderson, Alessio Farcomeni, Maria Grazia Pittau, Roberto Zelli · Journal of the Royal Statistical Society Series C (Applied Statistics) · 2018
Summary A latent Markov model admitting variation in the number of latent states at each time period is introduced. The model facilitates subjects switching latent states at each time period according to an inhomogeneous first-order Markov process, wherein transition matrices are generally rectangular. As a consequence, latent groups can merge, split or be rearranged. An application analysing the progress of wellbeing of nations, as measured by the three dimensions of the human development index over the last 25 years, illustrates the approach.