statsmodels.sandbox.distributions.transformed.TransfTwo_gen¶
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class
statsmodels.sandbox.distributions.transformed.TransfTwo_gen(kls, func, funcinvplus, funcinvminus, derivplus, derivminus, *args, **kwargs)[source]¶ Distribution based on a non-monotonic (u- or hump-shaped transformation)
the constructor can be called with a distribution class, and functions that define the non-linear transformation. and generates the distribution of the transformed random variable
Note: the transformation, it’s inverse and derivatives need to be fully specified: func, funcinvplus, funcinvminus, derivplus, derivminus. Currently no numerical derivatives or inverse are calculated
This can be used to generate distribution instances similar to the distributions in scipy.stats.
Attributes
random_stateGet or set the RandomState object for generating random variates. Methods
__call__(\*args, \*\*kwds)Freeze the distribution for the given arguments. cdf(x, \*args, \*\*kwds)Cumulative distribution function of the given RV. entropy(\*args, \*\*kwds)Differential entropy of the RV. expect([func, args, loc, scale, lb, ub, ...])Calculate expected value of a function with respect to the distribution. fit(data, \*args, \*\*kwds)Return MLEs for shape, location, and scale parameters from data. fit_loc_scale(data, \*args)Estimate loc and scale parameters from data using 1st and 2nd moments. freeze(\*args, \*\*kwds)Freeze the distribution for the given arguments. interval(alpha, \*args, \*\*kwds)Confidence interval with equal areas around the median. isf(q, \*args, \*\*kwds)Inverse survival function (inverse of sf) at q of the given RV. logcdf(x, \*args, \*\*kwds)Log of the cumulative distribution function at x of the given RV. logpdf(x, \*args, \*\*kwds)Log of the probability density function at x of the given RV. logsf(x, \*args, \*\*kwds)Log of the survival function of the given RV. mean(\*args, \*\*kwds)Mean of the distribution. median(\*args, \*\*kwds)Median of the distribution. moment(n, \*args, \*\*kwds)n-th order non-central moment of distribution. nnlf(theta, x)Return negative loglikelihood function. pdf(x, \*args, \*\*kwds)Probability density function at x of the given RV. ppf(q, \*args, \*\*kwds)Percent point function (inverse of cdf) at q of the given RV. rvs(\*args, \*\*kwds)Random variates of given type. sf(x, \*args, \*\*kwds)Survival function (1 - cdf) at x of the given RV. stats(\*args, \*\*kwds)Some statistics of the given RV. std(\*args, \*\*kwds)Standard deviation of the distribution. var(\*args, \*\*kwds)Variance of the distribution. Methods
cdf(x, \*args, \*\*kwds)Cumulative distribution function of the given RV. entropy(\*args, \*\*kwds)Differential entropy of the RV. expect([func, args, loc, scale, lb, ub, ...])Calculate expected value of a function with respect to the distribution. fit(data, \*args, \*\*kwds)Return MLEs for shape, location, and scale parameters from data. fit_loc_scale(data, \*args)Estimate loc and scale parameters from data using 1st and 2nd moments. freeze(\*args, \*\*kwds)Freeze the distribution for the given arguments. interval(alpha, \*args, \*\*kwds)Confidence interval with equal areas around the median. isf(q, \*args, \*\*kwds)Inverse survival function (inverse of sf) at q of the given RV. logcdf(x, \*args, \*\*kwds)Log of the cumulative distribution function at x of the given RV. logpdf(x, \*args, \*\*kwds)Log of the probability density function at x of the given RV. logsf(x, \*args, \*\*kwds)Log of the survival function of the given RV. mean(\*args, \*\*kwds)Mean of the distribution. median(\*args, \*\*kwds)Median of the distribution. moment(n, \*args, \*\*kwds)n-th order non-central moment of distribution. nnlf(theta, x)Return negative loglikelihood function. pdf(x, \*args, \*\*kwds)Probability density function at x of the given RV. ppf(q, \*args, \*\*kwds)Percent point function (inverse of cdf) at q of the given RV. rvs(\*args, \*\*kwds)Random variates of given type. sf(x, \*args, \*\*kwds)Survival function (1 - cdf) at x of the given RV. stats(\*args, \*\*kwds)Some statistics of the given RV. std(\*args, \*\*kwds)Standard deviation of the distribution. var(\*args, \*\*kwds)Variance of the distribution. Attributes
random_stateGet or set the RandomState object for generating random variates.
