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In the frequentist approach to inference, statistical procedures are assessed by their performance over a hypothetical long run of repetitions of a process deemed to have generated the data.
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What if the MVUE depends on the parameter?
What if we have a strictly frequentist perspective? … As I mention in the comments, it seems weird that a frequentist would completely have to abandon the MVUE criterion in these "degenerate" cases, while a Bayesian could easily make sense of them too by …
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Frequentism and priors
In this sense, the frequentist view is simpler, you only have a model and some data. …
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Bayesian and frequentist optimization and intervals
I realize the methodology pursued by the Frequentist and Bayesian camps generally differ. … Edit:
Actually, the optimization bit of my question is a bit misleading, as it is only a specific example of differences between Bayesian and Frequentist thinking. …
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Under which conditions do Bayesian and frequentist point estimators coincide?
With a flat prior, the ML (frequentist -- maximum likelihood) and the MAP (Bayesian -- maximum a posteriori) estimators coincide. … Here, $\mathbf{D}$ seems to be known as data/design matrix in the frequentist/Bayesian lingo, respectively. …