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#: ../../source/reference/tensor/generated/mars.tensor.random.standard_cauchy.rst:2
msgid "mars.tensor.random.standard\\_cauchy"
msgstr ""

#: mars.tensor.random.standard_cauchy:1 of
msgid "Draw samples from a standard Cauchy distribution with mode = 0."
msgstr ""

#: mars.tensor.random.standard_cauchy:3 of
msgid "Also known as the Lorentz distribution."
msgstr ""

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

#: mars.tensor.random.standard_cauchy:5 of
msgid ""
"Output shape.  If the given shape is, e.g., ``(m, n, k)``, then ``m * n *"
" k`` samples are drawn.  Default is None, in which case a single value is"
" returned."
msgstr ""

#: mars.tensor.random.standard_cauchy:9 of
msgid "Desired chunk size on each dimension"
msgstr ""

#: mars.tensor.random.standard_cauchy:11 of
msgid "Allocate the tensor on GPU if True, False as default"
msgstr ""

#: mars.tensor.random.standard_cauchy:13 of
msgid "Data-type of the returned tensor."
msgstr ""

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

#: mars.tensor.random.standard_cauchy:16 of
msgid "**samples** -- The drawn samples."
msgstr ""

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

#: mars.tensor.random.standard_cauchy:20 of
msgid "Notes"
msgstr ""

#: mars.tensor.random.standard_cauchy:21 of
msgid "The probability density function for the full Cauchy distribution is"
msgstr ""

#: mars.tensor.random.standard_cauchy:23 of
msgid ""
"P(x; x_0, \\gamma) = \\frac{1}{\\pi \\gamma \\bigl[ 1+ "
"(\\frac{x-x_0}{\\gamma})^2 \\bigr] }"
msgstr ""

#: mars.tensor.random.standard_cauchy:26 of
msgid ""
"and the Standard Cauchy distribution just sets :math:`x_0=0` and "
":math:`\\gamma=1`"
msgstr ""

#: mars.tensor.random.standard_cauchy:29 of
msgid ""
"The Cauchy distribution arises in the solution to the driven harmonic "
"oscillator problem, and also describes spectral line broadening. It also "
"describes the distribution of values at which a line tilted at a random "
"angle will cut the x axis."
msgstr ""

#: mars.tensor.random.standard_cauchy:34 of
msgid ""
"When studying hypothesis tests that assume normality, seeing how the "
"tests perform on data from a Cauchy distribution is a good indicator of "
"their sensitivity to a heavy-tailed distribution, since the Cauchy looks "
"very much like a Gaussian distribution, but with heavier tails."
msgstr ""

#: mars.tensor.random.standard_cauchy:40 of
msgid "References"
msgstr ""

#: mars.tensor.random.standard_cauchy:41 of
msgid ""
"NIST/SEMATECH e-Handbook of Statistical Methods, \"Cauchy Distribution\","
" http://www.itl.nist.gov/div898/handbook/eda/section3/eda3663.htm"
msgstr ""

#: mars.tensor.random.standard_cauchy:44 of
msgid ""
"Weisstein, Eric W. \"Cauchy Distribution.\" From MathWorld--A Wolfram Web"
" Resource. http://mathworld.wolfram.com/CauchyDistribution.html"
msgstr ""

#: mars.tensor.random.standard_cauchy:47 of
msgid ""
"Wikipedia, \"Cauchy distribution\" "
"http://en.wikipedia.org/wiki/Cauchy_distribution"
msgstr ""

#: mars.tensor.random.standard_cauchy:51 of
msgid "Examples"
msgstr ""

#: mars.tensor.random.standard_cauchy:52 of
msgid "Draw samples and plot the distribution:"
msgstr ""

