Parameterization of the Weibull distribution for network meta-analysis

Source: R/distributions.R

Density, distribution function, hazards, quantile function and random generation for the Weibull distribution when parameterized for network meta-analysis.

dweibullNMA(x, a0, a1 = FALSE, log = FALSE)

pweibullNMA(q, a0, a1, lower.tail = TRUE, log.p = FALSE)

qweibullNMA(p, a0, a1, lower.tail = TRUE, log.p = FALSE)

rweibullNMA(n, a0, a1)

hweibullNMA(n, a0, a1, log = FALSE)

HweibullNMA(n, a0, a1, log = FALSE)

rmst_weibullNMA(t, a0, a1, start = 0)

mean_weibullNMA(a0, a1)

Arguments

x, q

Vector of quantiles

a0

Intercept of reparameterization of the Weibull distribution.

a1

Slope of the reparameterization of the Weibull distribution.

log, log.p

logical; if TRUE, probabilities p are given as log(p).

lower.tail

logical; if TRUE (default), probabilities are \(P(X \le x)\), otherwise, \(P(X > x)\).

p

Vector of probabilities

n

Number of observations. If length(n) > 1, the length is taken to be the number required.

t

Vector of times for which restricted mean survival time is evaluated.

start

Optional left-truncation time or times. The returned restricted mean survival will be conditional on survival up to this time.

Value

dweibullNMA gives the density, pweibullNMA gives the distribution function, qweibullNMA gives the quantile function, rweibullNMA generates random deviates, HweibullNMA returns the cumulative hazard and hweibullNMA the hazard.

See also

dweibull