Prior_lambda {brr} | R Documentation |
Density, distribution function (see Details) and random generation for the prior distribution on
the rate in the treated group. The prior distribution on the incidence rate \lambda
is not to
be set by the user: it is induced by the user-specified prior on \mu
and \phi
.
dprior_lambda(lambda, a, b, c, d, S, T)
rprior_lambda(n, a, b, c, d, S, T)
pprior_lambda(q, a, b, c, d, S, T, ...)
sprior_lambda(a, b, c, d, S, T, ...)
lambda , q |
vector of quantiles |
a , b |
non-negative shape and rate parameter of the Gamma prior distribution on |
c , d |
non-negative shape parameters of the prior distribution on |
S , T |
sample sizes in control group and treated group |
n |
number of observations to be simulated |
... |
other arguments passed to |
The pdf of the prior distribution on the incidence rate \lambda
involves
the Kummer confluent hypergeometric function of the second kind.
The cdf involves the generalized hypergeometric function. Its current implementation
does not work when a-c
is an integer.
dprior_lambda
gives the density, pprior_lambda
the distribution function
(see Details), rprior_lambda
samples from the distribution, and
rprior_lambda
gives a summary of the distribution.
Prior_lambda
is a generic name for the functions documented.
curve(dprior_lambda(x, 2, 2, 2.5, 2, 10, 10), from=0, to=5)
sprior_lambda(2, 2, 2.5, 2, 10, 10)