# SOME DESCRIPTIVE TITLE.
# Copyright (C) 1999-2020, The Alibaba Group Holding Ltd.
# This file is distributed under the same license as the mars package.
# FIRST AUTHOR <EMAIL@ADDRESS>, 2020.
#
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"Project-Id-Version: mars 0.5.0a2\n"
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"POT-Creation-Date: 2020-06-16 16:57+0800\n"
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"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
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#: ../../source/reference/tensor/generated/mars.tensor.random.laplace.rst:2
msgid "mars.tensor.random.laplace"
msgstr ""

#: mars.tensor.random.laplace:1 of
msgid ""
"Draw samples from the Laplace or double exponential distribution with "
"specified location (or mean) and scale (decay)."
msgstr ""

#: mars.tensor.random.laplace:4 of
msgid ""
"The Laplace distribution is similar to the Gaussian/normal distribution, "
"but is sharper at the peak and has fatter tails. It represents the "
"difference between two independent, identically distributed exponential "
"random variables."
msgstr ""

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

#: mars.tensor.random.laplace:9 of
msgid "The position, :math:`\\mu`, of the distribution peak. Default is 0."
msgstr ""

#: mars.tensor.random.laplace:11 of
msgid ":math:`\\lambda`, the exponential decay. Default is 1."
msgstr ""

#: mars.tensor.random.laplace:13 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 ``loc`` and ``scale`` are both scalars. Otherwise, "
"``np.broadcast(loc, scale).size`` samples are drawn."
msgstr ""

#: mars.tensor.random.laplace:18 of
msgid "Desired chunk size on each dimension"
msgstr ""

#: mars.tensor.random.laplace:20 of
msgid "Allocate the tensor on GPU if True, False as default"
msgstr ""

#: mars.tensor.random.laplace:22 of
msgid "Data-type of the returned tensor."
msgstr ""

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

#: mars.tensor.random.laplace:25 of
msgid "**out** -- Drawn samples from the parameterized Laplace distribution."
msgstr ""

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

#: mars.tensor.random.laplace:29 of
msgid "Notes"
msgstr ""

#: mars.tensor.random.laplace:30 of
msgid "It has the probability density function"
msgstr ""

#: mars.tensor.random.laplace:32 of
msgid ""
"f(x; \\mu, \\lambda) = \\frac{1}{2\\lambda} \\exp\\left(-\\frac{|x - "
"\\mu|}{\\lambda}\\right)."
msgstr ""

#: mars.tensor.random.laplace:35 of
msgid ""
"The first law of Laplace, from 1774, states that the frequency of an "
"error can be expressed as an exponential function of the absolute "
"magnitude of the error, which leads to the Laplace distribution. For many"
" problems in economics and health sciences, this distribution seems to "
"model the data better than the standard Gaussian distribution."
msgstr ""

#: mars.tensor.random.laplace:43 of
msgid "References"
msgstr ""

#: mars.tensor.random.laplace:44 of
msgid ""
"Abramowitz, M. and Stegun, I. A. (Eds.). \"Handbook of Mathematical "
"Functions with Formulas, Graphs, and Mathematical Tables, 9th printing,\""
" New York: Dover, 1972."
msgstr ""

#: mars.tensor.random.laplace:47 of
msgid ""
"Kotz, Samuel, et. al. \"The Laplace Distribution and Generalizations, \" "
"Birkhauser, 2001."
msgstr ""

#: mars.tensor.random.laplace:49 of
msgid ""
"Weisstein, Eric W. \"Laplace Distribution.\" From MathWorld--A Wolfram "
"Web Resource. http://mathworld.wolfram.com/LaplaceDistribution.html"
msgstr ""

#: mars.tensor.random.laplace:52 of
msgid ""
"Wikipedia, \"Laplace distribution\", "
"http://en.wikipedia.org/wiki/Laplace_distribution"
msgstr ""

#: mars.tensor.random.laplace:56 of
msgid "Examples"
msgstr ""

#: mars.tensor.random.laplace:57 of
msgid "Draw samples from the distribution"
msgstr ""

#: mars.tensor.random.laplace:64 of
msgid ""
"Display the histogram of the samples, along with the probability density "
"function:"
msgstr ""

#: mars.tensor.random.laplace:73 of
msgid "Plot Gaussian for comparison:"
msgstr ""

