You have built a simulation model, but now must choose runs to i) validate it, and ii) to gain insight about the associated real system and to make managerial recommendations. Do you need guidance?

This repository contains an implementation of the graphical method in Python, designed by Davian Bermudez. The graphical method is a technique used in linear programming to solve optimization problems ...

Heckerman, D. (1998) A tutorial on learning with Bayesian networks, learning in graphical models. Kluwer Academic Publishers, Dordrecht, 301-354.

Probabilistic graphical models are useful for modelling stochastic phenomena for doing inferences and reasoning under uncertainty. Especially, chain graph models and Bayesian networks can be used as ...

IT has been anticipated for some time that Mr. Barker would publish an account of the graphical and tabular methods in crystallography which he has been teaching at Oxford, and that his book would ...

Hubbert’s graphical-heuristic method (1956) Cavallo’s article begins, “It is well known that M. K. Hubbert (in 1956) successfully predicted the timing (1970) of peak US oil production.

A new method for handling the data from a series of biochemical oxygen demand dilutions consists of graphing the dissolved oxygen remaining in each dilution verus the volume of sample added. The ...

Suggested here is a simple graphical method for studying the goodness of fit in Cox's regression model for survival data. The method is easy to use, as it does not require the estimation of ...

In this paper we introduce five graphical statistical methods to compare countries level of development relative to other countries and across time. For this, we use seven panels of data on the Human ...