Sentence examples for a single component model from inspiring English sources

For the distribution of CpGO/E values, a two-component mixture model provided substantially better fit than a single component model [Additional file 1] and as a consequence, we modeled the distribution with a two-component model.

Interestingly, a single component model failed to fit the data when the enhancer sites become more and more densely clustered while a two-component model fits the entire range of cluster density data well.

We found that a two-component model provided substantially better fit than a single component model [see Additional file 1 for trace of BIC for different numbers of components].

Thus, the signal model may be simplified to a single-component model.

Because of the dominance of the major microviscosity, one could argue that the minor microviscosity should be ignored and a single-component model used instead.

The fit of a single-component model and a two-component model to our data was calculated with AICs (second-order, or corrected for sample size).

The slope of the decay on the correlated data is the reason the single-component model (fcs, τD ∼ 6.85 ms) does not fit the crowded data and appears too high to the left of the point of inflection, G τD), and too low to the right, so we discard a single-component model as inappropriate to fit this data.

It has been shown that, for a single component PLS model, the first weight vector, w1, provides the best estimate of the importance of a given variable, for describing the response.

Under both basal and 100 nM NPY treated conditions, photon counting histograms for Y1-sfGFP cell data (Fig. 8A, B) were generated by 1 ms bins, and described sufficiently by a single component PCH model.

These concentrations were derived by fitting the red and green autocorrelation curves to a single component diffusion model and dividing the obtained number of particles by the red and green confocal volumes ('Materials and methods').

The autocorrelation curves of these FCS data were then fitted to a single component diffusion model: (1) G = 1 N · 1 (1 + τ τ D ) 1 + τ s 2 · τ D + G ∞ where s is the structural parameter, G ∞ is the offset, and N is the average number of particles in the confocal volume, in order to derive τ D. FRAP measurements were performed on a Zeiss LSM 510 META using a 40x 1.2 NA water objective at 37°C.