In this tutorial we demonstrate how one can use TKRISK to analyze vaccine response to COVID19. We create a simple model of contamination and show how vaccine and exposition can jointly affect the probability of being infected.
We review with this example the logic and applicability of Bayesian networks. We are able to closely match the analytical solution thanks to efficient sampling methods including low discrepancy sequences. This is the first of a three parts demo.
In this tutorial we demonstrate how one can use TKRISK to analyze vaccine response to COVID19. We create a simple model of contamination and show how vaccine and exposition can jointly affect the probability of being infected.
We review with this example the logic and applicability of Bayesian networks. We are able to closely match the analytical solution thanks to efficient sampling methods including low discrepancy sequences. This is the first of a three parts demo.
DISTRIBUTION FITTER
Tenokonda Distribution Fitter returns the most likely distribution from a set of input observations.
Features

Ranking of most likely distributions from over 30 different distributions

Handles lower/upper bound truncated distributions

Choice of goodness of fit measures

Flexible constraints handling on any parameters

Specific penalty weight setting
References
[1] H. Cramér, "Mathematical methods of statistics" , Princeton Univ. Press (1946)
[2] Claeskens, G.; Hjort, N. L. (2008), Model Selection and Model Averaging, Cambridge University Press
[3] HuberCarol, C.; Balakrishnan, N.; Nikulin, M. S.; Mesbah, M., eds. (2002), GoodnessofFit Tests and Model Validity, Springer
[4] Cressie, N. and Read, T. R. C., “Multinomial GoodnessofFit Tests”, J. Royal Stat. Soc. Series B, Vol. 46, No. 3 (1984), pp. 440464.