The regression equation of the designed experiment was obtained by applying four models namely linear, interactive, quadratic and cubic models which were fitted to the experimental data obtained from the design system.
We applied two models using very different approaches, one Bayesian (Weiner process) and one frequentist (Spline model).
This study relied on a solar resource evaluation that utilized data from two solar atlases and one meteorological station, the latter to which we applied two models.
To elucidate the role of HO-1 induction we applied two models i) pharmacological inhibition of HO-1 using SnPPIX and ii) HO-1 deficient mice.
We applied two models to test how our outcome was affected by PPI therapy, which could be attributed to ulcer prophylaxis: one conservative model, where all patients who redeemed a prescription of an NSAID or antiplatelet drug were censored.
We applied two models (Poisson-Gamma and BYM), with and without spatially structured random terms, which may help the reader to appraise different data summaries with different etiological clues (see Elliott et al., 2000 and Lawson et al., 1999).
Also, the developed code applies three models for simulation: single porosity single permeability, dual porosity single permeability, and dual permeability dual porosity.
We applied three models to perform genomic predictions that fit all the SNP simultaneously.
In our study, we applied seven models with different event cost schemes.
For complete time series, we then fit eight models (two smoothers and four sets of df for seasonality control) in each city for lags 0 and 1, whereas we applied six models (two smoothers and three sets of df) in cities with systematically missing data for lag 1 analysis.
