Date of Completion

Spring 5-1-2014

Thesis Advisor(s)

Nalini Ravishanker

Honors Major



Applied Mathematics | Longitudinal Data Analysis and Time Series | Mathematics | Other Applied Mathematics | Other Mathematics | Statistics and Probability


This thesis proposes a method of finding initial parameter estimates in the Log ACD1 model for use in recursive estimation. The recursive estimating equations method is applied to the Log ACD1 model to find recursive estimates for the unknown parameters in the model. A literature review is provided on the ACD and Log ACD models, and on the theory of estimating equations. Monte Carlo simulations indicate that the proposed method of finding initial parameter estimates is viable. The parameter estimation process is demonstrated by fitting an ACD model and a Log ACD model to a set of IBM stock duration data.