Bayes - Medreonet
Bayes - Medreonet
Bayes - Medreonet
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Second order bayesian inference<br />
Tested= 50<br />
Positive = 3<br />
Sensitivity of the test= 93%<br />
Sum(Posterior) / Sum<br />
Specificity of the test= 95%<br />
Binomial likelihood<br />
Posterior<br />
True positives<br />
True positives<br />
Infected animals 0 1 2 3 0 1 2 3<br />
in the sample Prior 0,25 0,25 0,25 0,25 0,25 0,25 0,25 0,25 Normalized posterior<br />
0 0,019608 0,219875 0 0 0 0,001078 0 0 0 0,258188132<br />
1 0,019608 0,015229 0,24538 0 0 7,47E-05 0,001203 0 0 0,306020881<br />
2 0,019608 0,001053 0,034685 0,186289 0 5,16E-06 0,00017 0,000913 0 0,260715921<br />
3 0,019608 7,28E-05 0,003674 0,040322 0,072187 3,57E-07 1,8E-05 0,000198 0,000354 0,136512804<br />
4 0,019608 5,02E-06 0,000346 0,005816 0,021276 2,46E-08 1,69E-06 2,85E-05 0,000104 0,032224319<br />
49 0,019608 0 0 2,67E-53 1,05E-49 0 0 1,31E-55 5,17E-52 1,23862E-49<br />
50 0,019608 0 0 0 8,27E-51 0 0 0 4,05E-53 9,70674E-51
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