Abstract
Stochastic compartmental models are widely used in modeling processes such as drug kinetics in biological systems. This paper considers the distribution of the residence times for stochastic multi-compartment models, especially systems with non-exponential lifetime distributions. The paper first derives the moment generating function of the bivariate residence time distribution for the two-compartment model with general lifetimes and approximates the density of the residence time using the saddlepoint approximation. Then, it extends the distributional approach to the residence time for multi-compartment semi-Markov models combining the cofactor rule for a single destination and the analytic approach to the two-compartment model. This approach provides a complete specification of the residence time distribution based on the moment generating function and thus facilitates an easier calculation of high-order moments than the approach using the coefficient matrix. Applications to drug kinetics demonstrate the simplicity and usefulness of this approach.
| Original language | English |
|---|---|
| Pages (from-to) | 185-205 |
| Number of pages | 21 |
| Journal | Mathematical Biosciences |
| Volume | 191 |
| Issue number | 2 |
| DOIs | |
| State | Published - Oct 2004 |
Keywords
- Cofactor rule
- Moment generating function
- Residence time
- Saddlepoint approximation
- Semi-Markov process
- Stochastic compartment model
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