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@ -106,7 +106,7 @@ __all__ = [
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'levy_stable', 'logistic', 'loggamma', 'loglaplace', 'lognorm',
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'levy_stable', 'logistic', 'loggamma', 'loglaplace', 'lognorm',
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'gilbrat', 'maxwell', 'mielke', 'nakagami', 'ncx2', 'ncf', 't',
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'gilbrat', 'maxwell', 'mielke', 'nakagami', 'ncx2', 'ncf', 't',
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'nct', 'pareto', 'lomax', 'powerlaw', 'powerlognorm', 'powernorm',
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'nct', 'pareto', 'lomax', 'powerlaw', 'powerlognorm', 'powernorm',
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'rdist', 'rayleigh', 'reciprocal', 'rice', 'recipinvgauss',
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'rdist', 'rayleigh', 'truncrayleigh','reciprocal', 'rice', 'recipinvgauss',
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'semicircular', 'triang', 'truncexpon', 'truncnorm',
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'semicircular', 'triang', 'truncexpon', 'truncnorm',
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'tukeylambda', 'uniform', 'vonmises', 'wald', 'wrapcauchy',
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'tukeylambda', 'uniform', 'vonmises', 'wald', 'wrapcauchy',
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'entropy', 'rv_discrete',
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'entropy', 'rv_discrete',
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@ -5177,6 +5177,40 @@ for x >= 0.
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"""
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"""
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)
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)
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class truncrayleigh_gen(rv_continuous):
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def link(self, x, logSF, phat, ix):
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rv_continuous.link.__doc__
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c = phat[0]
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if ix == 1:
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return x - phat[1] / sqrt(-2.0 * logSF)
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else:
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return x - phat[2] * sqrt(-2.0 * logSF)
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def _pdf(self, r, c):
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rc = r+c
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return rc*exp(-(rc*rc-c*c)/2.0)
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def _cdf(self, r, c):
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rc = r+c
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return - expm1(-(rc*rc-c*c)/ 2.0)
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def _ppf(self, q, c):
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return sqrt(c*c - 2 * log1p(-q)) - c
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def _stats(self, c):
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val = 4-pi
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return np.sqrt(pi/2), val/2, 2*(pi-3)*sqrt(pi)/val**1.5, \
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6*pi/val-16/val**2
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def _entropy(self, c):
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return _EULER/2.0 + 1 - 0.5*log(2)
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truncrayleigh = truncrayleigh_gen(a=0.0, name="truncrayleigh",
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longname="A truncated Rayleigh",
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shapes='c',
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extradoc="""
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Truncated Rayleigh distribution
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truncrayleigh.cdf(r) = 1 - exp(-((r+c)**2-c**2)/2)
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for x >= 0.
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"""
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)
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# Reciprocal Distribution
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# Reciprocal Distribution
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class reciprocal_gen(rv_continuous):
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class reciprocal_gen(rv_continuous):
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def _argcheck(self, a, b):
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def _argcheck(self, a, b):
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