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Team:NTNU Trondheim/Modeling
From 2011.igem.org
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=== Bayesian Hierarchy === | === Bayesian Hierarchy === | ||
| - | We den wish to model the reliability for the observations... That is the probability of false positive/negative results P(RTF = 1|stress) and opposite. | + | We den wish to model the reliability for the observations... That is the probability of false positive/negative results |
| - | Having the observations x_i, i = 0,1,...,n, and y_j , j = 0,1,...,m, were x_i is under condition C = 1 (stress) , and y_j is under condition C = 0 (no stress). | + | <math> |
| + | P(RTF = 1|stress) | ||
| + | </math> | ||
| + | and opposite. | ||
| + | Having the observations | ||
| + | x_i, i = 0,1,...,n, and y_j , j = 0,1,...,m, | ||
| + | |||
| + | were x_i is under condition C = 1 (stress) , and y_j is under condition C = 0 (no stress). | ||
=== Linear Classification === | === Linear Classification === | ||
Revision as of 14:57, 24 June 2011
Models are under construction -------Page
3 types of models: Systems of ODE, Bayesian hierarchy and linear classification problems (LDA or similar). To be continued....
Contents |
Model Introduction
-What to model
-How to model
The Models
Systems of ODE
Bayesian Hierarchy
We den wish to model the reliability for the observations... That is the probability of false positive/negative results <math> P(RTF = 1|stress) </math> and opposite. Having the observations x_i, i = 0,1,...,n, and y_j , j = 0,1,...,m,
were x_i is under condition C = 1 (stress) , and y_j is under condition C = 0 (no stress).
