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fixed pymc.Kumaraswamy docsting (#5550)
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pymc/distributions/continuous.py

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@@ -1349,9 +1349,9 @@ class Kumaraswamy(UnitContinuous):
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Parameters
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----------
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a: float
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a : tensor_like of float
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a > 0.
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b: float
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b : tensor_like of float
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b > 0.
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"""
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rv_op = kumaraswamy
@@ -1378,9 +1378,9 @@ def logp(value, a, b):
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Parameters
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----------
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value: numeric
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value : tensor_like of float
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Value(s) for which log-probability is calculated. If the log probabilities for multiple
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values are desired the values must be provided in a numpy array or Aesara tensor
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values are desired the values must be provided in a numpy array or Aesara tensor.
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Returns
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-------
@@ -1406,7 +1406,7 @@ def logcdf(value, a, b):
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Parameters
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----------
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value: numeric or np.ndarray or aesara.tensor
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value : tensor_like of float
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Value(s) for which log CDF is calculated. If the log CDF for
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multiple values are desired the values must be provided in a numpy
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array or Aesara tensor.

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