Returns L(u, v).

r""" The (restricted) mean survival time: the area under the estimated survival function from 0 to tau. If the survival funct

r""" Calculates the mean of the Exponential distribution with given parameters. .. math:: E = \frac{1}{\lambda}

r""" Mean of the four-parameter Beta distribution .. math:: E = a + \left(b - a\right)\frac{\alpha}{\alpha + \beta}

Central finite-difference Hessian of a scalar ``func`` at ``x``. Used to approximate the observed Fisher information from the negative lo

r""" Quantile function of the non-parametric estimate. Returns the smallest observed value at which the estimated CDF reaches, or

r""" Quantile function for the LogNormal Distribution: .. math:: q(p) = e^{\mu + \sigma \Phi^{-1} \left( p \right )}

r""" Quantile function for the Beta Distribution: Parameters ---------- p : numpy array or scalar The p

r""" Quantile function for the Normal Distribution: .. math:: q(p) = \Phi^{-1} \left( p \right ) Parameters

r""" Quantile function for the four-parameter Beta distribution: .. math:: q(p) = a + \left(b - a\right) I^{-1}_{p}\left

Currently limited to only Mean Order Number Room to expand to: Modal Order Number, and Median Order Number Uses mean order statis

r""" Survival (or Reliability) function for the Exponential Distribution: .. math:: R(x) = e^{-\lambda x} Param

r""" Surival (or Reliability) function for a distribution using the parameters found in the ``.params`` attribute. Parameters

Simulate time-terminated recurrence data based on the fitted model. Parameters ---------- T: float Time

Log of the probability mass within each observation's truncation interval, summed over the truncated rows. The likelihood of a truncated obse

The cumulative hazard function for a distribution using the parameters found in the ``.params`` attribute. Parameters

r""" Cumulative hazard rate for the Weibull Distribution: .. math:: h(x) = \frac{x}{\alpha}^{\beta} Parameters

r""" Cumulative hazard rate for the Logistic distribution: .. math:: H(x) = -\\ln \\left( R(x) \\right) Paramet

r""" Cumulative hazard rate for the LogNormal Distribution: .. math:: H(x) = -\ln \left ( R(x) \right ) Paramet

r""" Instantaneous hazard rate for the Uniform Distribution: .. math:: H(x) = \ln \left ( b - a \right ) - \ln \left ( b

r""" Cumulative hazard rate for the LogLogistic Distribution: .. math:: H(x) = -\ln \left ( R(x) \right ) Param

r""" Cumulative hazard rate for the Gamma Distribution: .. math:: H(x) = -\ln(1 - \frac{\gamma \left ( \alpha, \beta x \

r""" Cumulative hazard rate for the Normal Distribution: .. math:: H(x) = -\ln \left( 1 - \Phi \left( \frac{x - \mu}{\si

r""" Cumulative hazard function for the Binomial distribution: .. math:: H(x) = -\ln R(x) Parameters --

r""" Cumulative hazard rate for the Exponential Distribution. .. math:: f(x) = \lambda x Parameters ---

r""" Cumulative hazard rate for the four-parameter Beta distribution. .. math:: H(x) = -\ln\left(R(x)\right) Pa

r""" Cumulative hazard rate for the Rayleigh Distribution: .. math:: H(x) = \frac{x^2}{2\sigma^2} Parameters

r""" Instantaneous hazard rate for the ExpoWeibull Distribution: .. math:: H(x) = -\ln \left ( R(x) \right ) Pa

r""" The cumulative hazard function for a distribution using the parameters found in the ``.params`` attribute. Parameters

Create a Proportional Hazards fitter for the given distribution. Uses exp(beta'Z) as the hazard multiplier — the standard parameterisation

Initialize a SurpyvalData instance for survival analysis. Validates, sorts, and stores survival data in the xcnt format. Supports unc