Parameter Estimation - ML vs. MAP - fu-berlin.de
ParameterEstimationPeter NRobinsonEstimatingParametersfrom DataMaximumLikelihood(ML)EstimationBetad istributionMaximum aposteriori(MAP)EstimationMAQParameter EstimationML vs. MAPPeter N RobinsonDecember 14, 2012ParameterEstimationPeter NRobinsonEstimatingParametersfrom DataMaximumLikelihood(ML)EstimationBetad istributionMaximum aposteriori(MAP)EstimationMAQEstimating 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.
(before seeing data) into a posterior probability, p( jX), by using the likelihood function p(Xj ). ... by asking people he meets at the Wall Street Golf Club1 which party they plan on voting for in the next election ... The probability that the value of lies between a and b is given by integrating the pdf over this region. Parameter Estimation ...
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