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This method is a two-stage subsampling-extrapolation bandwidth selection procedure, which is realized by first evaluating the risk at a fictional sample size m(m≤sample sizen) and then extrapolating the optimal bandwidth from m to n.
This simple first-order extrapolation estimator is equivalent to the rescaled "bagging-CV" bandwidth selector in Hall and Robinson (2009) if one sets the bootstrap size equal to the fictional sample size.
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These fictional samples consisted of interviews, diary entries, and various newspaper clippings, photos and book references forming the character biographies of all major Carnivàle characters.
And as we pause to consider the approach of another, very real ending, here is a random sampling of fictional ones from the bloody, bullet-riddled shelves of the Greenwich Village mystery bookstore Partners and Crime: "Everybody watched them to the door, and then turned back to their quiet speculations".
Most of The KLF's work was highly self-referential: lyrics were usually enigmatic narratives of The KLF's real and fictional exploits, and vocal samples were re-used in a variety of musical contexts.
To select the optimal choice of the fictional size m given a sample of size n, we propose a nested cross-validation methodology.
The samples of the fictional rum brand, Duque, which will run in the next issue of Rolling Stone, are described by the network as delivering the taste of a nonalcoholic lime Mojito "without the sugar, calories or alcohol".
Portraits of Freddie Mercury, Pokémon parodies, and a milk monstrosity attacking a fictional metropolis are just a sampling of what Farrimond does with the medium.
For example, a CoClear sample report involving a fictional yogurt company revealed that coconut milk was the top ingredient contributor to greenhouse gas emissions for a particular product line, making up 37.14% of the total.
Study course and sample collection times in a fictional morning patient.
13613_2017_251_MOESM4_ESM.pdf Additional file 4: Figure S3B Study course and sample collection times in a fictional afternoon patient.
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