Abstract
In this paper we introduce a simple framework which provides a basis for estimating parameters and testing statistical hypotheses in complex models. The only assumption that is made in the model describing the process under study, is that the deviations of the observations from the model have a multivariate normal distribution. The application of the statistical techniques presented in this paper may have considerable utility in the analysis of a wide variety of complex biological and epidemiological models. To our knowledge, the model and methods described here have not previously been published in the area of theoretical immunology.
| Original language | English |
|---|---|
| Pages (from-to) | 1131-1139 |
| Number of pages | 9 |
| Journal | Bulletin of Mathematical Biology |
| Volume | 65 |
| Issue number | 6 |
| DOIs | |
| State | Published - Nov 2003 |
Bibliographical note
Funding Information:We are grateful to Dr M Cancro for the collaboration of B cell development and the use of the data, and to Dr A Neumann for useful discussions. Supported in part by Israel Science Foundation—The Dorot Science Fellowship Foundation grant number 759/01-1, The Yigal Alon Fellowship, and a Bar-Ilan University internal grant (to RM).
Funding
We are grateful to Dr M Cancro for the collaboration of B cell development and the use of the data, and to Dr A Neumann for useful discussions. Supported in part by Israel Science Foundation—The Dorot Science Fellowship Foundation grant number 759/01-1, The Yigal Alon Fellowship, and a Bar-Ilan University internal grant (to RM).
| Funders | Funder number |
|---|---|
| Dorot Science Fellowship Foundation | 759/01-1 |
| Yigal Alon Fellowship | |
| Bar-Ilan University | |
| Israel Science Foundation |