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Parameter Estimation - ML vs. MAP - fu-berlin.de

ParameterEstimationPeter NRobinsonEstimatingParametersfrom DataMaximumLikelihood(ML)EstimationBetad istributionMaximum aposteriori(MAP)EstimationMAQP arameter EstimationML vs. MAPP eter N RobinsonDecember 14, 2012 ParameterEstimationPeter NRobinsonEstimatingParametersfrom DataMaximumLikelihood(ML)EstimationBetad istributionMaximum aposteriori(MAP)EstimationMAQE stimating parameters from DataIn many situations in bioinformatics, we want to estimate op-timal parameters from data. In the examples we have seen inthe lectures on variant calling, these parameters might be theerror rate for reads, the proportion of a certain genotype, theproportion of nonreference bases etc.

by asking people he meets at the Wall Street Golf Club1 which party they plan on voting for in the next election The statistician asks 100 people, seven of whom answer \Democrats". This can be modeled as a series of Bernoullis, just like the coin tosses. In this case, the maximum likelihood estimate of the

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