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#: ../../source/reference/tensor/generated/mars.tensor.random.gamma.rst:2
msgid "mars.tensor.random.gamma"
msgstr ""

#: mars.tensor.random.gamma:1 of
msgid "Draw samples from a Gamma distribution."
msgstr ""

#: mars.tensor.random.gamma:3 of
msgid ""
"Samples are drawn from a Gamma distribution with specified parameters, "
"`shape` (sometimes designated \"k\") and `scale` (sometimes designated "
"\"theta\"), where both parameters are > 0."
msgstr ""

#: mars.tensor.random.gamma of
msgid "Parameters"
msgstr ""

#: mars.tensor.random.gamma:7 of
msgid "The shape of the gamma distribution. Should be greater than zero."
msgstr ""

#: mars.tensor.random.gamma:9 of
msgid ""
"The scale of the gamma distribution. Should be greater than zero. Default"
" is equal to 1."
msgstr ""

#: mars.tensor.random.gamma:12 of
msgid ""
"Output shape.  If the given shape is, e.g., ``(m, n, k)``, then ``m * n *"
" k`` samples are drawn.  If size is ``None`` (default), a single value is"
" returned if ``shape`` and ``scale`` are both scalars. Otherwise, "
"``np.broadcast(shape, scale).size`` samples are drawn."
msgstr ""

#: mars.tensor.random.gamma:17 of
msgid "Desired chunk size on each dimension"
msgstr ""

#: mars.tensor.random.gamma:19 of
msgid "Allocate the tensor on GPU if True, False as default"
msgstr ""

#: mars.tensor.random.gamma:21 of
msgid "Data-type of the returned tensor."
msgstr ""

#: mars.tensor.random.gamma of
msgid "Returns"
msgstr ""

#: mars.tensor.random.gamma:24 of
msgid "**out** -- Drawn samples from the parameterized gamma distribution."
msgstr ""

#: mars.tensor.random.gamma of
msgid "Return type"
msgstr ""

#: mars.tensor.random.gamma:29 of
msgid ":func:`scipy.stats.gamma`"
msgstr ""

#: mars.tensor.random.gamma:30 of
msgid ""
"probability density function, distribution or cumulative density "
"function, etc."
msgstr ""

#: mars.tensor.random.gamma:33 of
msgid "Notes"
msgstr ""

#: mars.tensor.random.gamma:34 of
msgid "The probability density for the Gamma distribution is"
msgstr ""

#: mars.tensor.random.gamma:36 of
msgid "p(x) = x^{k-1}\\frac{e^{-x/\\theta}}{\\theta^k\\Gamma(k)},"
msgstr ""

#: mars.tensor.random.gamma:38 of
msgid ""
"where :math:`k` is the shape and :math:`\\theta` the scale, and "
":math:`\\Gamma` is the Gamma function."
msgstr ""

#: mars.tensor.random.gamma:41 of
msgid ""
"The Gamma distribution is often used to model the times to failure of "
"electronic components, and arises naturally in processes for which the "
"waiting times between Poisson distributed events are relevant."
msgstr ""

#: mars.tensor.random.gamma:46 of
msgid "References"
msgstr ""

#: mars.tensor.random.gamma:47 of
msgid ""
"Weisstein, Eric W. \"Gamma Distribution.\" From MathWorld--A Wolfram Web "
"Resource. http://mathworld.wolfram.com/GammaDistribution.html"
msgstr ""

#: mars.tensor.random.gamma:50 of
msgid ""
"Wikipedia, \"Gamma distribution\", "
"http://en.wikipedia.org/wiki/Gamma_distribution"
msgstr ""

#: mars.tensor.random.gamma:54 of
msgid "Examples"
msgstr ""

#: mars.tensor.random.gamma:55 of
msgid "Draw samples from the distribution:"
msgstr ""

#: mars.tensor.random.gamma:62 of
msgid ""
"Display the histogram of the samples, along with the probability density "
"function:"
msgstr ""

