Tessero\Stats\Uniform

__construct(mixed $a = 0.0, mixed $b = 1.0)

pdf(mixed $x): Tessero\NDArray|float

logpdf(mixed $x): Tessero\NDArray|float

cdf(mixed $x): Tessero\NDArray|float

logcdf(mixed $x): Tessero\NDArray|float

ccdf(mixed $x): Tessero\NDArray|float

Complementary CDF — the survival function (scipy ccdf == legacy sf).

logccdf(mixed $x): Tessero\NDArray|float

log of the complementary CDF (scipy logccdf == legacy logsf).

icdf(mixed $p): Tessero\NDArray|float

Inverse CDF — the quantile / percent-point function (scipy icdf == legacy ppf).

iccdf(mixed $p): Tessero\NDArray|float

Inverse complementary CDF (scipy iccdf == legacy isf).

ilogcdf(mixed $y): Tessero\NDArray|float

Inverse of logcdf: icdf(exp(y)).

ilogccdf(mixed $y): Tessero\NDArray|float

Inverse of logccdf: iccdf(exp(y)).

mean(): Tessero\NDArray|float

median(): Tessero\NDArray|float

variance(): Tessero\NDArray|float

standard_deviation(): Tessero\NDArray|float

skewness(): Tessero\NDArray|float

The skewness — 0 for every uniform.

kurtosis(): Tessero\NDArray|float

The Pearson (NON-excess) kurtosis: the RV API returns the full fourth standardized moment, which is the legacy excess kurtosis (stats('k') = -1.2) plus 3 (= 1.8 for every uniform).

entropy(): Tessero\NDArray|float

mode(): Tessero\NDArray|float

The mode — any point in [a, b]; scipy returns the interval midpoint (a + b) / 2.

support(): array

moment(int $order, string $kind = 'raw'): Tessero\NDArray|float

The raw ('raw' — non-central), 'central' or 'standardized' moment of the given order.