NEXTNetR supports a series of pre-defined distributions for transmission and recover/reset time, and also allows custom distributions to be defined with userdefined_time.
Each time_distribution object actually represents a two-parameer family
of distributions, see time_functions for a full discussion and for functions
that operate on time distribution objects.
Usage
exponential_time(lambda, p_infinity = 0)
lognormal_time(mean, var, p_infinity = 0)
gamma_time(mean, var, p_infinity = 0)
weibull_time(shape, scale, p_infinity = 0)
polynomial_rate_time(coeffs)
deterministic_time(tau)Value
exponential_time(lambda, p_infinity). Returns a time distribution representing an exponential distribution with ratelambdawhich in addition to finite values produces the value infinity with probabilityp_infinity.lognormal_time(mean, var, p_infinity). Returns a time distribution representing a Log-normal distribution with the givenmeanandvariance, which in addition to finite values produces the value infinity with probabilityp_infinity.gamma_time(mean, var, p_infinity). Returns a time distribution representing a Gamma distribution with the givenmeanandvariance, which in addition to finite values produces the value infinity with probabilityp_infinity.weibull_time(mean, var, p_infinity). Returns a time distribution representing a Weibull distribution with the givenshapeandscaleparameter, which in addition to finite values produces the value infinity with probabilityp_infinity. The distribution has mean \(b \Gamma(1 + 1/a)\) and variance \(b^2(\Gamma(1 + 2/a) - \Gamma^2(1 + 1/a))\)for shape \(a\) and scale \(b\).polynomial_rate_time(coeffs). Distribution with survival function \(\Psi(\tau) = e^{-p(\tau)}\) for a polynomial hazard rate \(p = c[1] + c[2] x + c[3] x^2 + \ldots\) with non-negative coefficients.deterministic_time(tau). Deterministic time with fixed valuetau