Under-reported data analysis with INAR-hidden Markov chains

作者：Fernandez Fontelo Amanda^*; Cabana Alejandra; Puig Pedro; Morina David

来源：Statistics in Medicine, 2016, 35(26): 4875-4890.

DOI：10.1002/sim.7026

• discrete time series
• emission probabilities
• integer-autoregressive models
• thinning operator
• under-recorded data

In this work, we deal with correlated under-reported data through INAR(1)-hidden Markov chain models. These models are very flexible and can be identified through its autocorrelation function, which has a very simple form. A naive method of parameter estimation is proposed, jointly with the maximum likelihood method based on a revised version of the forward algorithm. The most-probable unobserved time series is reconstructed by means of the Viterbi algorithm. Several examples of application in the field of public health are discussed illustrating the utility of the models.

• 出版日期2016-10