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# This file is distributed under the same license as the mars package.
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#: ../../source/reference/tensor/generated/mars.tensor.random.logseries.rst:2
msgid "mars.tensor.random.logseries"
msgstr ""

#: mars.tensor.random.logseries:1 of
msgid "Draw samples from a logarithmic series distribution."
msgstr ""

#: mars.tensor.random.logseries:3 of
msgid ""
"Samples are drawn from a log series distribution with specified shape "
"parameter, 0 < ``p`` < 1."
msgstr ""

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

#: mars.tensor.random.logseries:6 of
msgid "Shape parameter for the distribution.  Must be in the range (0, 1)."
msgstr ""

#: mars.tensor.random.logseries:8 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 ``p`` is a scalar.  Otherwise, ``np.array(p).size`` samples "
"are drawn."
msgstr ""

#: mars.tensor.random.logseries:13 of
msgid "Desired chunk size on each dimension"
msgstr ""

#: mars.tensor.random.logseries:15 of
msgid "Allocate the tensor on GPU if True, False as default"
msgstr ""

#: mars.tensor.random.logseries:17 of
msgid "Data-type of the returned tensor."
msgstr ""

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

#: mars.tensor.random.logseries:20 of
msgid ""
"**out** -- Drawn samples from the parameterized logarithmic series "
"distribution."
msgstr ""

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

#: mars.tensor.random.logseries:25 of
msgid ":func:`scipy.stats.logser`"
msgstr ""

#: mars.tensor.random.logseries:26 of
msgid ""
"probability density function, distribution or cumulative density "
"function, etc."
msgstr ""

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

#: mars.tensor.random.logseries:30 of
msgid "The probability density for the Log Series distribution is"
msgstr ""

#: mars.tensor.random.logseries:32 of
msgid "P(k) = \\frac{-p^k}{k \\ln(1-p)},"
msgstr ""

#: mars.tensor.random.logseries:34 of
msgid "where p = probability."
msgstr ""

#: mars.tensor.random.logseries:36 of
msgid ""
"The log series distribution is frequently used to represent species "
"richness and occurrence, first proposed by Fisher, Corbet, and Williams "
"in 1943 [2].  It may also be used to model the numbers of occupants seen "
"in cars [3]."
msgstr ""

#: mars.tensor.random.logseries:42 of
msgid "References"
msgstr ""

#: mars.tensor.random.logseries:43 of
msgid ""
"Buzas, Martin A.; Culver, Stephen J.,  Understanding regional species "
"diversity through the log series distribution of occurrences: "
"BIODIVERSITY RESEARCH Diversity & Distributions, Volume 5, Number 5, "
"September 1999 , pp. 187-195(9)."
msgstr ""

#: mars.tensor.random.logseries:47 of
msgid ""
"Fisher, R.A,, A.S. Corbet, and C.B. Williams. 1943. The relation between "
"the number of species and the number of individuals in a random sample of"
" an animal population. Journal of Animal Ecology, 12:42-58."
msgstr ""

#: mars.tensor.random.logseries:51 of
msgid ""
"D. J. Hand, F. Daly, D. Lunn, E. Ostrowski, A Handbook of Small Data "
"Sets, CRC Press, 1994."
msgstr ""

#: mars.tensor.random.logseries:53 of
msgid ""
"Wikipedia, \"Logarithmic distribution\", "
"http://en.wikipedia.org/wiki/Logarithmic_distribution"
msgstr ""

#: mars.tensor.random.logseries:57 of
msgid "Examples"
msgstr ""

#: mars.tensor.random.logseries:58 of
msgid "Draw samples from the distribution:"
msgstr ""

#: mars.tensor.random.logseries:67 of
msgid "#   plot against distribution"
msgstr ""

