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written by
Spencer Wheaton
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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**- 138kb Adobe PDF Document*MCIntegration_No2_ImportanceSamplingSampleMean.pdf*

Last Modified *March 8, 2014*

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

**Download**- 151kb Adobe PDF Document*No1_HitMissSampleMean.pdf*

Last Modified *March 8, 2014*

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This file is included in the full-text index.
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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**- 1852kb Java Archive File*MCIntegration_No1_1DHitMissSampleMean.jar*

Last Modified *March 8, 2014*

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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**- 1862kb Java Archive File*MCIntegration_No2_1DImpSampAndSampleMean.jar*

Last Modified *March 8, 2014*

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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**- 12kb Compressed File*ejs_src_No1_1DHitMissSampleMean.zip*

Last Modified *March 8, 2014*

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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**- 10kb Compressed File*ejs_src_No2_1DImpSampAndSampleMean.zip*

Last Modified *March 8, 2014*

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