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The S1 statistic is not dependent on the eigenvectors' ordering per se because it is based on comparisons within eigenvector, i.e., on the difference between the amount of variance explained by one eigenvector from one sample in the original and reciprocal samples.
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The experimental degree of continuity was shown to have a linear dependence on the reciprocal of sample thickness.
The reciprocal of sample entropy was taken as the fitness function and variable evolutionary coefficients were employed.
Titers are expressed as the reciprocal of sample dilution.
One Illumina Genome Analyzer run of each reciprocal F1 sample was run on the Illumina Genome Analyzer.
The number of plaques was multiplied by the reciprocal of sample dilution and converted to p.f.u./g.
Weighting will reflect the reciprocal of sampling probability.
As we show in the simulations below the reciprocal importance sampler is suitable for the comparatively simple models which we investigate in this study.
The OI was the reciprocal serum sample dilution yielding 50% killing compared with the growth in control wells containing no serum.
The reciprocal importance sampler was shown to perform well [ 18] when compared to other model comparison methods such as reversible jump MCMC or simple information criteria like the BIC.
However, if a sample of S sample points θ1,..., θ S, from the posterior distribution p(θ | Y, M) is available (for example, from an MCMC simulation), then the model evidence can be estimated by Gelfand and Dey's [ 17] reciprocal importance sampler, which is defined as (3) where h(θ | M) is an arbitrary probability density function over parameters θ.
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