Probabilistic graphical models are a powerful technique for handling uncertainty in machine learning. The course will cover how probability distributions can be represented in graphical models, how ...

Sufficient dimension-reduction methods provide effective ways to visualize discriminant analysis problems. For example, Cook and Yin showed that the dimension-reduction method of sliced average ...

A graphical procedure is given to evaluate the sample size for which confidence intervals of specified lengths, for the parameters of the multinomial distribution, are simultaneously verified at a ...

Engage students remotely or in the lab with advanced data analysis and take advantage of the special introductory site license price of $69 Expanding upon its award-winning Vernier Graphical Analysis™ ...

Learn to address the likelihood of structural failure. Perform risk analysis associated with environmental loads to structures under static and dynamic loadings. Master the basics of performance-based ...

For planning studies that consider risk and reliability, it is useful to run ensembles of hydrologic inputs and perform statistical analysis on the results to get probabilistic output, much like a ...

In SIGMATEK's web-based visualization tool, the LASAL VISUDesigner, two new controls are available to make life easier for the user: the Data Logger for process analysis and the Interpreter for ...