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

#: mars.tensor.random.wald:1 of
msgid "Draw samples from a Wald, or inverse Gaussian, distribution."
msgstr ""

#: mars.tensor.random.wald:3 of
msgid ""
"As the scale approaches infinity, the distribution becomes more like a "
"Gaussian. Some references claim that the Wald is an inverse Gaussian with"
" mean equal to 1, but this is by no means universal."
msgstr ""

#: mars.tensor.random.wald:7 of
msgid ""
"The inverse Gaussian distribution was first studied in relationship to "
"Brownian motion. In 1956 M.C.K. Tweedie used the name inverse Gaussian "
"because there is an inverse relationship between the time to cover a unit"
" distance and distance covered in unit time."
msgstr ""

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

#: mars.tensor.random.wald:12 of
msgid "Distribution mean, should be > 0."
msgstr ""

#: mars.tensor.random.wald:14 of
msgid "Scale parameter, should be >= 0."
msgstr ""

#: mars.tensor.random.wald:16 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 ``mean`` and ``scale`` are both scalars. Otherwise, "
"``np.broadcast(mean, scale).size`` samples are drawn."
msgstr ""

#: mars.tensor.random.wald:21 of
msgid "Desired chunk size on each dimension"
msgstr ""

#: mars.tensor.random.wald:23 of
msgid "Allocate the tensor on GPU if True, False as default"
msgstr ""

#: mars.tensor.random.wald:25 of
msgid "Data-type of the returned tensor."
msgstr ""

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

#: mars.tensor.random.wald:28 of
msgid "**out** -- Drawn samples from the parameterized Wald distribution."
msgstr ""

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

#: mars.tensor.random.wald:32 of
msgid "Notes"
msgstr ""

#: mars.tensor.random.wald:33 of
msgid "The probability density function for the Wald distribution is"
msgstr ""

#: mars.tensor.random.wald:35 of
msgid ""
"P(x;mean,scale) = \\sqrt{\\frac{scale}{2\\pi x^3}}e^ "
"\\frac{-scale(x-mean)^2}{2\\cdotp mean^2x}"
msgstr ""

#: mars.tensor.random.wald:38 of
msgid ""
"As noted above the inverse Gaussian distribution first arise from "
"attempts to model Brownian motion. It is also a competitor to the Weibull"
" for use in reliability modeling and modeling stock returns and interest "
"rate processes."
msgstr ""

#: mars.tensor.random.wald:44 of
msgid "References"
msgstr ""

#: mars.tensor.random.wald:45 of
msgid ""
"Brighton Webs Ltd., Wald Distribution, http://www.brighton-"
"webs.co.uk/distributions/wald.asp"
msgstr ""

#: mars.tensor.random.wald:47 of
msgid ""
"Chhikara, Raj S., and Folks, J. Leroy, \"The Inverse Gaussian "
"Distribution: Theory : Methodology, and Applications\", CRC Press, 1988."
msgstr ""

#: mars.tensor.random.wald:50 of
msgid ""
"Wikipedia, \"Wald distribution\" "
"http://en.wikipedia.org/wiki/Wald_distribution"
msgstr ""

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

#: mars.tensor.random.wald:55 of
msgid "Draw values from the distribution and plot the histogram:"
msgstr ""

