This mixture distribution method and the method based on curve-fitting of translation function derived from mapping of cumulative distribution functions are illustrated to be capable of capturing the upper tail of translation function, thus lead to satisfactory estimations of extreme statistics for a variety of non-Gaussian processes.
Finally, many different kinds of multimodal function problems are illustrated to certify the applicability of the presented method, including one maximum and one minimum, two maximums and two minimums, multiple maximums and multiple minimums, and a complex engineering optimization problem with inequality conditions.
Implementation of these equations is illustrated to generate the numerical data as functions of the variables such as the pressure difference across the membrane, methanol concentration at the cell anode, temperature, and position in the membrane.
The description of the expressed genes and distribution of gene functions was illustrated according to GO analysis and KEGG assignment.
Also, the relevance of gain of function or loss of function should have been illustrated in this context.
Examples to show the existence of α-univex functions have also been illustrated.
The description of the expressed genes and their functions was illustrated according to annotation and GO assignment.
For evaluating the proposed model, the residual values, which are defined as the natural logarithm of the ratio of the observed value to that predicted, are illustrated as a function of the hypocentral distance (Figs. 8(a) and 8(c)).
This paper combines exploratory spatial data analysis and input output method to explore the spatial pattern of key industrial co-agglomerations in Beijing, which is illustrated by location, function, frequency, spatial hierarchy and spacing.
The power gain in the transmitted region is illustrated as a function of angle for frequencies below the first cut-off.
