Sentence examples for statistical models by from inspiring English sources

Minimal between-batch variability was accounted for in statistical models by including BatchID as a random effect.

The average of the forecasts of the dynamical models is shown by the thick yellow line, and of the statistical models by the thick green line.

Statistical models, by contrast, do not use physical equations, but rather statistical formulations that produce forecasts based on a long history of past observations of (a) what is being predicted (e.g., the Niño3.4 SST anomaly), and (b) relevant predictors (e.g., sea level pressure patterns, tropical Pacific subsurface temperatures, or even the Niño3.4 SST itself).

However, no effective method is available yet for the determination of the associated model parameters such as the tortuosity factor q. Considering the analogy between water flow and electrical current flow in a porous medium, in this study, we proposed to improve the predictive capability of statistical models by determining the tortuosity factor q using electrical conductivity (EC) measurements.

It can avoid any assumptions on statistical models by utilizing fuzzy rules to determine the magnitudes of α and β.

In addition from this sample, we can compute and observe correlations between parameters, produce desired plot of the marginal posterior distributions, etc. Flexible software for Bayesian analysis of complex statistical models by using MCMC methods.

We modeled rates directly with a log-linear statistical model by including counts as the dependent outcome and population at risk as an offset term.

But evidence for that is unclear, and a statistical model by Yair Ghitza and Andrew Gelman found that preferences in politics are typically set at an early age, with lasting influence.

The latter extends a conventional signal quantisation statistical model by assuming a Gaussian distribution noise.

The earthquake simulator used in the study, RSQSim, simplifies California's statistical model by eliminating many of the assumptions that go into estimating the likelihood of an earthquake of a certain size hitting a specific region.

Further experiments are conducted to confirm the validity of the developed statistical model by comparing the model predictions with the experimental results.