Marginal probability of invasive listeriosis over r
DRLogNormPoisson.RdThe function DRLogNormPoisson() provides the marginal probability of invasive listeriosis
in a given population for a given Dose in CFU. this function is not vectorized.
Usage
DRLogNormPoisson(
Dose,
meanlog10,
sdlog10,
Poisson = FALSE,
low = -Inf,
up = Inf,
silent = TRUE,
tol = 1e-20,
method = "integrate",
...
)Arguments
- Dose
(
CFU/serving) Dose (scalar or vector). It should be integers ifPoissonisTRUE.- meanlog10
the meanlog10 parameter of the distribution of
r(parameter of the exponential model).- sdlog10
the sdlog10 parameter of the distribution of
r(parameter of the exponential model).- Poisson
if
TRUE, assume thatDoseis the mean of a Poisson distribution. (actual LogNormal Poisson). IfFALSE(default), assume thatDoseis the actual number of bacteria.- low
lower value for the integration.
- up
upper value for the integration.
- silent
silent the error-try function.
- tol
relative tolerance. Note: for
method = "cubature", the tolerance will be set to \(1E-05\).- method
either
"integrate"(default) or"cubature"to specify the integration method.- ...
further arguments to pass to the integrate function.
Details
The function evaluates
$$\int_{low}^{inf} \Phi(x, mulog_{10}, sdlog_{10})\cdot(1-e^{(-Dose \cdot 10^{r})}) dr$$
using the integrate function, with a relative tolerance equals to tol
if Poisson is TRUE. If Poisson is FALSE, it evaluates
$$\int_{low}^{inf} \Phi(x, mulog_{10}, sdlog_{10})\cdot(1-(1-10^{r})^{Dose}) dr$$.
For method = "cubature", the tolerance will be set to \(1E-5\).
method = "cubature" will use the \link[cubature]{hcubature} function that
is much slower but guarantees a tolerance of \(1E-5\).
Note
This function is used by the DR() function, a wrapper of DRLogNormPoisson().
For a quick, vectorized version of it, use DRQuick().
References
Pouillot R, Hoelzer K, Chen Y, Dennis SB (2015). “Listeria monocytogenes dose response revisited–incorporating adjustments for variability in strain virulence and host susceptibility.” Risk Analysis, 35(1), 90–108. doi:10.1111/risa.12235 .