written by Spencer Wheaton

This website contains a set of 2 simulations and accompanying worksheets that introduce the techniques of sample mean, hit and miss and importance sampling Monte Carlo integration.

• Download MCIntegration_No2_ImportanceSamplingSampleMean.pdf - 138kb Adobe PDF Document

Last Modified March 8, 2014

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A worksheet to accompany the EJS simulation MCIntegration No1 1DHitMissSampleMean.jar

• Download No1_HitMissSampleMean.pdf - 151kb Adobe PDF Document

Last Modified March 8, 2014

This file is included in the full-text index.

The Hit & Miss Sample Mean Model investigates Monte Carlo integration techniques. The user is able to input a 1D integrand and finite integration limits and specify the number of trials and the number of separate runs.  The simulation allows the user to study the dependence of the uncertainty/error on the number of trials.

• Download MCIntegration_No1_1DHitMissSampleMean.jar - 1852kb Java Archive File

Last Modified March 8, 2014

The Monte Carlo Integration wiht Importance Sampling Model implements the sample mean and importance sampling techniques of Monte Carlo integration. The user can input a 1D integrand and finite integration limits and specify the required Monte Carlo technique or techniques.

The importance sampling technique requires the user to input a normalized probability distribution p(x) that matches the integrand in its main features, and an associated transformation law x(y) that converts a uniform y in [0,1) into an x sampled according to p(x). The simulation does perform a check on the normalization of p(x), but the result may be inaccurate for distributions defined over a very large interval or those with strange behavior.  The number of trials and the number of separate runs can be chosen by the user.

• Download MCIntegration_No2_1DImpSampAndSampleMean.jar - 1862kb Java Archive File

Last Modified March 8, 2014

The source code zip archive contains an XML representation of the Hit & Miss Sample Mean Model.  Unzip this archive in your EjsS 5 workspace to compile and run this model using EjsS 5 or above.

• Download ejs_src_No1_1DHitMissSampleMean.zip - 12kb Compressed File

Last Modified March 8, 2014

The source code zip archive contains an XML representation of the Monte Carlo Integration wiht Importance Sampling Model.  Unzip this archive in your EjsS 5 workspace to compile and run this model using EjsS 5 or above.

• Download ejs_src_No2_1DImpSampAndSampleMean.zip - 10kb Compressed File

Last Modified March 8, 2014