Miscellaneous¶
Probability¶
- sdr.Q(x: ArrayLike) NDArray[float64]
Computes the CCDF of the standard normal distribution \(\mathcal{N}(0, 1)\)..
- sdr.Qinv(p: ArrayLike) NDArray[float64]
Computes the inverse CCDF of the standard normal distribution \(\mathcal{N}(0, 1)\).
- sdr.add_iid_rvs(X, ...) rv_histogram
Numerically calculates the distribution of the sum of \(n\) i.i.d. random variables \(X_i\).
- sdr.add_rvs(X: rv_continuous | rv_histogram, Y, ...) rv_histogram
Numerically calculates the distribution of the sum of two independent random variables \(X\) and \(Y\).
- sdr.subtract_rvs(X, ...) rv_histogram
Numerically calculates the distribution of the difference of two independent random variables \(X\) and \(Y\).
- sdr.multiply_rvs(X, ...) scipy.stats.rv_histogram
Numerically calculates the distribution of the product of two independent random variables \(X\) and \(Y\).
- sdr.min_iid_rvs(X, ...) rv_histogram
Numerically calculates the distribution of the minimum of \(n\) i.i.d. random variables \(X_i\).
- sdr.max_iid_rvs(X, ...) rv_histogram
Numerically calculates the distribution of the maximum of \(n\) i.i.d. random variables \(X_i\).
Data manipulation¶
- sdr.pack(x: ArrayLike, bpe: int, ...) NDArray[int_]
Packs a binary array into an array with multiple bits per element.
- sdr.unpack(x: ArrayLike, bpe: int, ...) NDArray[int_]
Unpacks an array with multiple bits per element into a binary array.