Distributions

pytensor.tensor.random.basic.chisquare(df, size=None, **kwargs)

Draw samples from a chisquare distribution.

The probability density function for chisquare in terms of the number of degrees of freedom \(k\) is:

\[f(x; k) = \frac{(1/2)^{k/2}}{\Gamma(k/2)} x^{k/2-1} e^{-x/2}\]

for \(k > 2\). \(\Gamma\) is the gamma function:

\[\Gamma(x) = \int_0^{\infty} t^{x-1} e^{-t} \mathrm{d}t\]

This variable is obtained by summing the squares \(k\) independent, standard normally distributed random variables.

Signature

() -> ()

param df:

The number \(k\) of degrees of freedom. Must be positive.

param size:

Sample shape. If the given size is, e.g. (m, n, k) then m * n * k independent, identically distributed random variables are returned. Default is None in which case a single random variable is returned.

pytensor.tensor.random.basic.choice(a, size=None, replace=True, p=None, rng=None)

Generate a random sample from an array.

Parameters:

• a – The array from which to randomly sample an element. If an int, a sample is generated from pytensor.tensor.arange(a).

• p – The probabilities associated with each entry in a. If not given, all elements have equal probability.

• replace – When True, sampling is performed with replacement.

• size – Sample shape. If the given size is (m, n, k), then m * n * k independent samples are returned. Default is None, in which case a single sample is returned.

pytensor.tensor.random.basic.permutation(x, **kwargs)

Randomly permute a sequence or a range of values.

Signature

() -> (x) if x is a scalar, (*x) -> (*x) otherwise

param x:

If x is an integer, randomly permute np.arange(x). If x is a sequence, shuffle its elements randomly.

pytensor.tensor.random.basic.standard_normal(*, size=None, rng=None, dtype=None)

Draw samples from a standard normal distribution.

Signature

nil -> ()

param size:

Sample shape. If the given size is, e.g. (m, n, k) then m * n * k independent, identically distributed random variables are returned. Default is None in which case a single random variable is returned.