f.Y.Weibull: Marginal density function for conditional Weibull random...
In mbannick/survDeconvolution: Survival Deconvolution

If !correlated: Y \sim Weibull(shape=p, rate=λ)
If correlated: Y \sim Weibull(shape=p, rate=λ \cdot k^{p}) \quad K \sim Gamma(a, b)

1	f.Y.Weibull(y, parameters, gamma_shape, gamma_rate, correlated)

`y`	A vector at which to evaluate the density function
`parameters`	A list of the two parameters of the Weibull distribution p and lambda before the re-parameterization described for `k` in `f.Weibull`.
`gamma_shape`	The shape parameter for gamma distribution where in `f.Weibull`, k ~ Gamma(gamma_shape, gamma_rate).
`gamma_rate`	The shape parameter for gamma distribution where in `f.Weibull`, k ~ Gamma(gamma_shape, gamma_rate).
`correlated`	If `FALSE`, then this is just a regular Weibull density that you could get with `dweibull`. If `TRUE`, then include the frailty parameterization marginalizing over `k` in `f.Weibull`.