Distributions¶
This section collects various additional functions and methods for statistical distributions.
Empirical Distributions¶
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Return the Empirical CDF of an array as a step function. |
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A basic step function. |
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Given a monotone function fn (no checking is done to verify monotonicity) and a set of x values, return an linearly interpolated approximation to its inverse from its values on x. |
Distribution Extras¶
Skew Distributions
univariate Skew-Normal distribution of Azzalini |
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univariate Skew-Normal distribution of Azzalini |
univariate Skew-T distribution of Azzalini |
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univariate Skew-Normal distribution of Azzalini |
Distributions based on Gram-Charlier expansion
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Return the Gaussian expanded pdf function given the list of central moments (first one is mean). |
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Return the Gaussian expanded pdf function given the list of 1st, 2nd moment and skew and Fisher (excess) kurtosis. |
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Return the Gaussian expanded pdf function given the list of central moments (first one is mean). |
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Gram-Charlier Expansion of Normal distribution |
cdf of multivariate normal wrapper for scipy.stats
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standardized multivariate normal cumulative distribution function |
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multivariate normal cumulative distribution function |
Univariate Distributions by non-linear Transformations¶
Univariate distributions can be generated from a non-linear transformation of an existing univariate distribution. Transf_gen is a class that can generate a new distribution from a monotonic transformation, TransfTwo_gen can use hump-shaped or u-shaped transformation, such as abs or square. The remaining objects are special cases.
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Distribution based on a non-monotonic (u- or hump-shaped transformation) |
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a class for non-linear monotonic transformation of a continuous random variable |
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Distribution based on log/exp transformation |
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Distribution based on log/exp transformation |
class to hold quadratic function with inverse function and derivative |
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Distribution based on a non-monotonic (u- or hump-shaped transformation) |
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a class for non-linear monotonic transformation of a continuous random variable |
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univariate distribution of a non-linear monotonic transformation of a random variable |
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a class for non-linear monotonic transformation of a continuous random variable |
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Distribution based on a non-monotonic (u- or hump-shaped transformation) |
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Distribution based on a non-monotonic (u- or hump-shaped transformation) |
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Distribution based on a non-monotonic (u- or hump-shaped transformation) |