Probabilistic Modeling

|

Models Illustrating Probabilistic Modeling

All the models assigned to the selected category are listed below.

You can filter the list by entering keywords or phrases into the search field:

  • Dashboard-Defined Distributions

    The purpose of this model is to allow an arbitrary cumulative or discrete distribution to be specified by entering values and probabilities in a Dashboard.

  • Risk Board Game

    These two models simulate different aspects of the classic board game Risk.

  • Ito-Process Random Walk Model

    A History Generator Element is used to model an Ito-process random walk. The distribution of the future value is lognormal with mean and variance that both increase linearly with time.

  • Markov Process Example Model

    Simple two state, continuous time Markov chain model which compares two theoretical probability distributions

  • Vector Distributions

    This example shows how a vector of sampled values can be generated from a single distribution definition for Sampled, Cumulative and Discrete stochastics

  • Indexing Data Records

    This model demonstrates two different ways to index a data record for use in a GoldSim model, either sequentially or randomly.

  • Defining Vector Distributions

    This example shows how to define and sample vector discrete and cumulative distributions using (1) a vector uniform 0-1 stochastic to sample probability levels and (2) a script element to get the corresponding values.

  • Export Statistical Histories to Excel

    For a Monte Carlo simulation, export statistical histories to Excel

  • Polya Urn Problem

    This simple model simulates the classic Polya urn problem in which stones, either black or white, are randomly selected (with replacement and addition) from a pot.

  • Time Shifting a Time Series

    The purpose of this model is to demonstrate time shifting historic data in a Time Series element. This type of model makes it easy to show summary statistics like exceedance probability of annual peak flow rate or mean annual flow rate.

  • Marketing Program Pick

    Three different types of promotional campaigns are compared across a 180 day campaign period.

  • Project Simulator

    This model illustrate how conditional containers can be used to simulate projects.

  • What-If Simulation Case Study

    Simple ECommerce, decision-making case study using GoldSim "what-if" simulation

  • Markov Process Rainfall Model

    This model simulates a Markov process that randomly switches between a wet state and a dry state to simulate rainfall given some key historic statistics.

  • Probabilistic Detention Pond Model

    This model presents a pond discharge versus pond capacity optimization problem.

  • Generation of a Stochastic Precipitation Record

    This model illustrates one way in which GoldSim can be used to generate a stochastic precipitation record.

  • Dam Breach Risk

    Monte Carlo Simulation of the Dam Breach algorithm to calculate risk of failure

  • Risk Assessment of Lunar Base

    This is a model that simulates the performance of a lunar base over its planned 20 year lifespan. It illustrates how GoldSim's Reliability Module can be use to carry out a probabilistic risk assessment of a complex system.

  • Risk Assessment of Planetary Mission

    This is a model that simulates an unmanned scientific mission to another planet. It illustrates how GoldSim's Reliability Module can be used to carry out a probabilistic risk assessment of a complex system.

  • Ships with Containers

    This model simulates ships entering the harbor where each ship carries a random number of containers.

  • Simulating Failure Risk of a Pump Station

    Use the Reliability Module of GoldSim to calculate the failure modes of various components of a pumping station and water delivery system.

 

Making Better Decisions In An Uncertain World