![]() ![]() The algorithm is effective due to the approximation of resistance using a three-parameter lognormal distribution. This class computes the same discrepancy as in . The algorithm for estimating the sensitivity indices is based on one loop of the Latin Hypercube Sampling method in combination with numerical integration. This class computes the same discrepancy as in 1 [see eq This abstract class is the base class of all discrepancy classes programmed with floating-point numbers with multi-precision This area is used to enrich the sample until the coefficient of Q2 of. Methods to compute various types of discrepancies for quasi-Monte Carlo point sets At the initial iteration, the sample is distributed according to a Latin hypercube. This class provides tools to create and manage curve plots This class provides tools to create and manage scatter plots This class implements QQ-plot (or quantile-quantile plot) objects that compare two probability distributions This class implements PP-plot (or probability-probability plot) objects that compare two probability distributions Provide tools to import and export data set tables to and from Gnuplot, MATLAB and Mathematica compatible formats, or customized format Provides tools to plot many datasets on the same chart This class provides tools to create and manage histograms This class provides additional tools to create and manage empirical plotsĪ renderer that draws horizontal lines between points and/or draws shapes at each data point to provide an empirical style chart The distributions supported are: normal, skewed normal, log-normal, Weibull, Gumbel, uniform, Discrete-Uniform and exponential. This component is easily extendable to other sampling methods through the plug-in framework. This class provides tools to plot the mass function and the cumulative probability of a discrete probability distribution over the integers Leverage simple random sampling, descriptive sampling, eight standard distributions, and distribution truncation. This class provides tools to plot the density and the cumulative probability of a continuous probability distributionĪ dataset that can be used for creating histograms This class provides tools to create charts from data in a simple way ![]() This class provides tools to create and manage box-and-whisker plots Represents an axis of a chart encapsulated by an instance of XYChart This class simulates a specific stochastic activity network with 9 nodes and 13 links, taken from Elmaghraby (1977) and used again in L'Ecuyer and Lemieux (2000), "Variance Reduction via Lattice Rules" ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |