Abstract
Let X(t) be a stochastic process which represents a health indicator of an individual. The mean level μ(t) = EX(t) is constant until the time t = S of infection and after infection it decreases according to some parametric function which may depend on covariate values measured on the individual. We model X(t) − μ(t) as a stationary Gaussian process and use data from cohort studies to obtain empirical Bayes estimators of the distribution of the change point S.
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Normand, SL.T., Doksum, K. (2001). Empirical Bayes Procedures for a Change Point Problem with Application to HIV/AIDS Data. In: Ahmed, S.E., Reid, N. (eds) Empirical Bayes and Likelihood Inference. Lecture Notes in Statistics, vol 148. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-0141-7_5
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DOI: https://doi.org/10.1007/978-1-4613-0141-7_5
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