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@ -50,7 +50,7 @@ __all__ = [
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'weibull_max', 'genlogistic', 'genpareto', 'genexpon', 'genextreme',
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'gamma', 'gengamma', 'genhalflogistic', 'gompertz', 'gumbel_r',
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'gumbel_l', 'halfcauchy', 'halflogistic', 'halfnorm', 'hypsecant',
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'gausshyper', 'invgamma', 'invnorm', 'invgauss', 'invweibull',
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'gausshyper', 'invgamma', 'invgauss', 'invweibull',
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'johnsonsb', 'johnsonsu', 'laplace', 'levy', 'levy_l',
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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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@ -3897,18 +3897,18 @@ class genpareto_gen(rv_continuous):
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self.b = where(c < 0, 1.0 / abs(c), inf)
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return where(abs(c) == inf, 0, 1)
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def _pdf(self, x, c):
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#%f = exp(-xn)/s; % for k==0
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#%f = exp(-xn)/s; % for k==0
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#%f = (1+k.*xn)**(-1./k-1)/s; % for k~=0
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#%f = exp((-1./k-1)*log1p(kxn))/s % for k~=0
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#%f = exp((-xn-kxn)*log1p(kxn)/(kxn))/s % for any k kxn~=inf
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return exp(self._logpdf(x, c)
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return exp(self._logpdf(x, c))
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#Px = pow(1+c*x,arr(-1.0-1.0/c))
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#return Px
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def _logpdf(self, x, c):
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cx = where((c == 0) & (x == inf), 0.0, c * x).clip(min= -1.0)
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def _logpdf(self, x, c):
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cx = where((c == 0) & (x == inf), 0.0, c * x).clip(min= -1.0)
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logpdf = where((cx == inf) | (cx == -1), -inf, -(x + cx) * log1pxdx(cx))
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putmask(logpdf, (c == -1) & (x == 1.0), 0.0)
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return logpdf
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return logpdf
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#return (-1.0-1.0/c) * np.log1p(c*x)
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def _chf(self, x, c):
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cx = c * x
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@ -5367,10 +5367,12 @@ class t_gen(rv_continuous):
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g1 = where(df > 3, 0.0, nan)
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g2 = where(df > 4, 6.0/(df-4.0), nan)
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return 0, mu2, g1, g2
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t = t_gen(name='t', shapes="df")
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## Non-central T distribution
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class nct_gen(rv_continuous):
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"""A non-central Student's T continuous random variable.
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@ -5714,7 +5716,7 @@ rayleigh = rayleigh_gen(a=0.0, name="rayleigh")
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class truncrayleigh_gen(rv_continuous):
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"""A truncated Rayleigh continuous random variable.
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"""A truncated Rayleigh continuous random variable.
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%(before_notes)s
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