Sentence examples for both simulated and empirical from inspiring English sources
Analyses on both simulated and empirical data were performed by using the general linear model with a shape assumed for sustained effects, but not transient effects.
In this paper, we begin by introducing the LCMV reconstruction formulation and then quantitatively assess its performance using both simulated and empirical data.
We analyzed both simulated and empirical data under a range of controlled conditions using both BI and this novel ML implementation.
In this paper, we describe a concrete implementation of this meta-Bayesian approach (i.e. a Bayesian treatment of Bayesian decision theoretic predictions) and demonstrate its utility by applying it to both simulated and empirical reaction time data from an associative learning task.
To compare the relationship between recombination similarities and genetic differentiation in the three populations being simulated and in the three corresponding HGDP populations, we performed a Spearman correlation of the values of recombination between all neighboring SNPs in the 1Mbp region and their FST values, for both simulated and empirical data.
The performance of EEEP was evaluated with both simulated and empirical data.
In both our simulated and empirical datasets, we show that the discovery of high-dimensional combinations and heterogeneity in the etiology of a complex disease may require not only computationally sophisticated algorithms but also careful examination and interpretation of the results of those algorithms to understand disease etiology.
In both the simulated and empirical datasets, a relatively small number of rate shifts, with rate conservation along lineages between shifts, are inferred by RLC.
In addition to testing our method, we analyze both our simulated and empirical data using one of the popular methods for species tree inference, BEST (Bayesian Estimation of Species Trees; [ 6]).
By using summary statistics, one can easily compare the simulated and empirical data in order to estimate parameters of the simulation model via an approximate sample of the posterior distribution.
Based on the results from p-distance and species identification analyses of simulated and empirical data, we decided to pick 500 loci for multilocus DNA barcoding.
