reconnect moved files to git repo

venv/lib/python3.11/site-packages/statsmodels/sandbox/distributions/try_max.py

@@ -0,0 +1,77 @@
+'''
+
+adjusted from Denis on pystatsmodels mailing list
+
+there might still be problems with loc and scale,
+
+'''
+
+from scipy import stats
+
+__date__ = "2010-12-29 dec"
+
+
+class MaxDist(stats.rv_continuous):
+    """ max of n of scipy.stats normal expon ...
+        Example:
+            maxnormal10 = RVmax( scipy.stats.norm, 10 )
+            sample = maxnormal10( size=1000 )
+            sample.cdf = cdf ^ n,  ppf ^ (1/n)
+    """
+
+    def __init__(self, dist, n):
+        self.dist = dist
+        self.n = n
+        extradoc = 'maximumdistribution is the distribution of the ' \
+                   + 'maximum of n i.i.d. random variable'
+        super().__init__(
+            name='maxdist', a=dist.a, b=dist.b, longname='A maximumdistribution'
+        )
+
+    def _pdf(self, x, *args, **kw):
+        return self.n * self.dist.pdf(x, *args, **kw) \
+            * self.dist.cdf(x, *args, **kw) ** (self.n - 1)
+
+    def _cdf(self, x, *args, **kw):
+        return self.dist.cdf(x, *args, **kw) ** self.n
+
+    def _ppf(self, q, *args, **kw):
+        # y = F(x) ^ n  <=>  x = F-1( y ^ 1/n)
+        return self.dist.ppf(q ** (1. / self.n), *args, **kw)
+
+
+##    def rvs( self, *args, **kw ):
+##       size = kw.pop( "size", 1 )
+##       u = np.random.uniform( size=size, **kw ) ** (1 / self.n)
+##       return self.dist.ppf( u, **kw )
+
+
+maxdistr = MaxDist(stats.norm, 10)
+
+print(maxdistr.rvs(size=10))
+print(maxdistr.stats(moments='mvsk'))
+
+'''
+>>> print maxdistr.stats(moments = 'mvsk')
+(array(1.5387527308351818), array(0.34434382328492852), array(0.40990510188513779), array(0.33139861783918922))
+>>> rvs = np.random.randn(1000,10)
+>>> stats.describe(rvs.max(1))
+(1000, (-0.028558517753519492, 3.6134958002753685), 1.5560520428553426, 0.34965234046170773, 0.48504309950278557, 0.17691859056779258)
+>>> rvs2 = maxdistr.rvs(size=1000)
+>>> stats.describe(rvs2)
+(1000, (-0.015290995091401905, 3.3227019151170931), 1.5248146840651813, 0.32827518543128631, 0.23998620901199566, -0.080555658370268013)
+>>> rvs2 = maxdistr.rvs(size=10000)
+>>> stats.describe(rvs2)
+(10000, (-0.15855091764294812, 4.1898138060896937), 1.532862047388899, 0.34361316060467512, 0.43128838106936973, 0.41115043864619061)
+
+>>> maxdistr.pdf(1.5)
+0.69513824417156755
+
+#integrating the pdf
+>>> maxdistr.expect()
+1.5387527308351729
+>>> maxdistr.expect(lambda x:1)
+0.99999999999999956
+
+
+'''