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| Overiew – Q-Pro 2.0 combines a simple math scripting language with the Monte-Carlo method to produce a powerful analysis tool. It is designed for engineers, scientists and academics who want to work with the Monte-Carlo method without the overhead and complexity of a programming language. Applications – Q-Pro 2.0 is a general purpose tool, applications include simulation, integration, estimation and distribution maths. The distribution package includes tutorials which are designed to get the user up and running with the software and to demonstrate the use of the program. MS Office interoperability – Many of the outputs can be exported into MS Office programs in the form of RTF, CSV and EMF either on the clipboard or in a file. Outputs – Depending on the application, the output for dependent variables includes the probability density distribution, cumulative curve, percentiles and distribution parameters (e.g. skewness and kurtosis). Scripting – Q-Pro 2.0 uses a subset of the VB Scripting language. The elements currently supported are: Math functions: abs, exp, fix, int, log, sgn, sqr. Trig functions: atn, sin, cos, tan. Flow control: if-elseif-else-end if. User defined functions: function, end function. Declarations: dim, const. Constants: PI. Comments: rem Distibutions – binomial (standard and normal approx.), exponential, gamma, logistic, lognormal (two versions), normal, pareto, poisson (standard and normal approx.) triangular, uniform (continuous) and the three parameter weibull. Randon number generation – The basic method is linear congruential with variations for shuffling and sorting. Evaluations and Termination – The number of evaluations for the Monte-Carlo process can be set to a value in the range 1,000 to 1,000,000. Convergent functions can be terminated when standard error of the mean of a selected variable is below a given value. Divergent functions can be terminated when then value of a select variable falls outside specified bounds. | |||||||||||
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Related Keywords for Q-Pro 2.0
Analysis Distributions Integration Maths Method Monte Carlo Monte-Carlo Simulation Statistics