numpy.polynomial.hermite_e.hermeweight()
  • References/Python/NumPy/Routines/Polynomials/Polynomial Package/HermiteE Module, “Probabilists’”

numpy.polynomial.hermite_e.hermeweight(x)

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numpy.busday_count()
  • References/Python/NumPy/Routines/Datetime Support Functions

numpy.busday_count(begindates, enddates, weekmask='1111100', holidays=[], busdaycal=None, out=None) Counts the number of

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numpy.corrcoef()
  • References/Python/NumPy/Routines/Statistics

numpy.corrcoef(x, y=None, rowvar=1, bias=, ddof=)

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numpy.ma.row_stack()
  • References/Python/NumPy/Routines/Masked array operations

numpy.ma.row_stack(tup) = Stack arrays in sequence vertically (row wise). Take a sequence of arrays and stack them vertically

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Chebyshev.identity()
  • References/Python/NumPy/Routines/Polynomials/Polynomial Package/Chebyshev Module

classmethod Chebyshev.identity(domain=None, window=None)

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RandomState.set_state()
  • References/Python/NumPy/Routines/Random sampling

RandomState.set_state(state) Set the internal state of the generator from a tuple. For use if one has

2025-01-10 15:47:30
RandomState.f()
  • References/Python/NumPy/Routines/Random sampling

RandomState.f(dfnum, dfden, size=None) Draw samples from an F distribution. Samples are drawn from an F distribution

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numpy.random.negative_binomial()
  • References/Python/NumPy/Routines/Random sampling

numpy.random.negative_binomial(n, p, size=None) Draw samples from a negative binomial distribution. Samples

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numpy.random.zipf()
  • References/Python/NumPy/Routines/Random sampling

numpy.random.zipf(a, size=None) Draw samples from a Zipf distribution. Samples are drawn from a Zipf distribution

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numpy.bmat()
  • References/Python/NumPy/Routines/Array creation routines

numpy.bmat(obj, ldict=None, gdict=None)

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