Sentence examples for model formulae are from inspiring English sources

The indexes, parameters and variables used in the model formulae are given in list of symbols.

Using the model, formulae are found for the distribution functions, the density functions, and the moments of crystal radii during nucleation and growth.

The influence of the parameters of the model on the optimum shapes is demonstrated and, for each model, formulae are derived relating the velocity of motion and the characteristics of the medium with the optimum angle.

The linear model formula is: y=ax+b (y, health indicator; x, BT consumption; a and b are the model calculated coefficients).

For example, for a trait with two QTL, the model formula was y ∼ Q1 + Q2 + Q1 Q2, where Q1 and Q2 represent the QTL objects corresponding to the markers at the maximum LOD scores of the significant QTL peaks.

The ADNEX model formula is given in supplementary appendix D. The effects of the predictors are presented as odds ratios in table 5. Proportion of solid tissue and serum CA-125 level had the strongest independent relations with the outcome, as judged by the test statistic for the model coefficients (not shown).

The form of the logistic model formula is: p = 1 / 1 + exp − B 0 + B 1 * X 1 + B 2 * X 2 + … + B k * X k where p is the probability that Y is 1, B0 is a constant (called the intercept), and B1 though Bk are the coefficients for the predictor variables X1 through Xk.

The accuracy of both the proposed analytical model and design formulae are validated by the results of two groups of axial tension tests, which demonstrates that the full-process load-strain behaviour can be accurately captured by a bilinear model based on the proposed analytical formulae.

Some mathematical models and engineering design formulae are proposed in order to calculate the tensile state and the fundamental design parameters of the main couplings, such as, for example, the fork steering shaft and the leg wheel pin couplings.

In post-hoc analyses, we evaluated the statistical significance of possible linear trend in the results for social class, education, and FH by using linear contrast in coefficients from stratified covariate-adjusted models and formulae were specific to each variable's number of levels (e.g. 5 for difficulty paying bills).

Statistical models and formulas are presented in the Appendix.