And Shortencarier, [9]) has been the most widely distributed mainframe version of the program. Commercial vendors of. LHS software include @RISK® and Crystal Ball®. Latin hypercube sampling is used worldwide in computer modeling applications related to performing safety assessments for geologic. Acronyms in Quality:: The Quality Portal. LAAmerican Association for Laboratory Accreditation. AARAppearance Approval Report. After Action Review.

Introduction Latin hypercube sampling (LHS) is a form of that can be applied to multiple variables. The method commonly used to reduce the number or runs necessary for a Monte Carlo simulation to achieve a reasonably accurate random distribution.

LHS can be incorporated into an existing Monte Carlo model fairly easily, and work with variables following any analytical probability distribution. Monte-Carlo simulations provide statistical answers to problems by performing many calculations with randomized variables, and analyzing the trends in the output data. There are many resources available describing (,, ).

The concept behind LHS is not overly complex. Variables are sampled using a even sampling method, and then randomly combined sets of those variables are used for one calculation of the target function. The sampling algorithm ensures that the distribution function is sampled evenly, but still with the same probability trend. Figure 1 and figure 2 demonstrate the difference between a pure random sampling and a stratified sampling of a log-normal distribution. (These figures were generated using different versions of the same software. Differences within the plot, such as the left axis label and the black lines, are due to ongoing development of the software application and are not related to the issue being demonstrated.) Figure 1.

A cumulative frequency plot of “recovery factor”, which was log-normally distributed with a mean of 60% and a standard deviation of 5%. Scarface World Is Yours Ps2 Iso Games. 500 samples were taken using the stratified sampling method described here, which generated a very smooth curve.

A cumulative frequency plot of “recovery factor”, which was log-normally distributed with a mean of 60% and a standard deviation of 5%. 500 random samples were taken. Process Sampling To perform the stratified sampling, the cumulative probability (100%) is divided into segments, one for each iteration of the Monte Carlo simulation.