SPIRRID - Tool for estimation of statistical characteristics of multivariate random functions (Python package)

SPIRRID - Tool for estimation of statistical characteristics of multivariate random functions (Python package)

Software

SPIRRID - Tool for estimation of statistical characteristics of multivariate random functions (Python package). The implementation of the SPIRRID is highly configurable and provides the following features: - The class SPIRRID can be configured for an arbitrary response function q(e = [], theta = []). The function q(e, theta) must be a "callable" object and must have one or more control variables e and one or more parameters theta. - The parameters and randomization are specified using the tvars trait attribute. They are instances of the RV class representing a random variable that can be associated with probabilistic distribution from scipy.stats.distribution package. - There are four sampling schemes that can be specified using the sampling_type trait attribute. - The execution of the integration may be done using the numpy implementation or using a compiled C-code implementation . - The control variable e can be n-dimensional

SPIRRID - Tool for estimation of statistical characteristics of multivariate random functions (Python package). The implementation of the SPIRRID is highly configurable and provides the following features: - The class SPIRRID can be configured for an arbitrary response function q(e = [], theta = []). The function q(e, theta) must be a "callable" object and must have one or more control variables e and one or more parameters theta. - The parameters and randomization are specified using the tvars trait attribute. They are instances of the RV class representing a random variable that can be associated with probabilistic distribution from scipy.stats.distribution package. - There are four sampling schemes that can be specified using the sampling_type trait attribute. - The execution of the integration may be done using the numpy implementation or using a compiled C-code implementation that gets generated on demand for the current response function and randomization scheme. - The control variable e can be n-dimensional, the range of the input array is specified using the evars parameter of the SPIRRID class. The statistical evaluation is performed for each combination of the entries contained in the range of the control variables. - The class SPIRRID can also calculate the variance along with the mean value. It can be easily extended with the evaluation of further characteristics like covariance or skewness. - State dependency between the attributes of the SPIRRID object is maintained automatically: If the input values and the configuration of the SPIRRID have been modified, the results get modified on demand upon the next access to the output values.

Python, Enthought traits, NumPy, SciPy, C, Loopless programming, Multidimensional integration, Estimation of statistical moments

Python, Enthought traits, NumPy, SciPy, C, Loopless programming, Multidimensional integration, Estimation of statistical moments

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only the provider uses the result

In order to use the result by another entity, it is always necessary to acquire a license

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