The kinetic parameters of the model were estimated via data fitting considering the effects of initial S2− concentration, S2−/NO3−-N ratio and Ac−-C/NO3−-N ratio.
The effect of diversity on wages can be estimated via panel data analysis that accounts for individual and regional effects over different time periods.
Typical rate expressions use a simple Arrhenius form for the rate constant with an activation energy Ed and pre-exponential factor ν. In the absence of experimental data, Ed can often be estimated via standard quantum methods.
For this purpose we took advantage of the thorough information available in a previous study [ 15], in which cadmium intake was assessed based on duplicate diets and the individual gastrointestinal absorption could be estimated via comprehensive data on iron status.
The orbit estimated using satellite data alone reasonably matched the one estimated via ground-based videos, the team reports online today in the Proceedings of the National Academy of Sciences.
Moreover, foliage clutter can be approximated as a narrowband Gaussian process [17 21], and the statistic characteristics in FSMR have empirically been estimated via the experimental data [18 20], thus the optimal detection procedure against clutter background in FSMR includes a whitening filter.
To account for non-normality of cost data, 95% confidence intervals (CI) were estimated via a non-parametric bootstrap approach using a percentile method based on 1,000 replications.
Model kinetic parameters are estimated via regression of cracking data obtained at temperatures relevant for industrial practice, 693 753 K.
In Section 3, the discrete macroeconomic model using generalized fractal derivative is discussed, and the coefficients are estimated via the actual macroeconomic data of the given country.
Table 2 presents the importance weights (i.e. parameter estimates) from choice models estimated from the conjoint analysis data using both a linear probability model (estimated via ordinary least squares) and logistic regression.
A DLDA classification rule was constructed from the complete training set data using the optimal number of genes estimated via the LOOCV stage of the analysis.
