A hands-on tutorial in Python for sensor engineers on Bayesian sensor calibration, which combines statistical models and data to optimally calibrate sensors. This technique is crucial in engineering to minimize sensor measurement uncertainty. The tutorial provides Python code to perform such calibration numerically using existing libraries.
Dirichlet is a conjugate prior to the Multinomial likelihood. In other words our posterior distr. is also a Dirichlet distributuion with parameters incorporating observed data.
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