ea_conc: Exposure assessment from concentration data

In brechtdv/QMRA: Parametric Models for Quantitative Microbial Risk Assessment

Description

Parametric modelling of exposure concentration from (possibly left-censored) concentration data.

Usage

ea_conc(x, d, data,
        model = c("gamma", "g",
                  "lognorm", "ln",
                  "weibull", "w",
                  "invgauss", "ig"),
        ...)

Arguments

x	The observed concentrations.
d	A vector indicating if the observations were left-censored (1) or not (0).
data	An optional data frame, containing the variables in the model. If not found in data, the variables are taken from the environment from which ea_count is called.
model	A character string naming the concentration model. See details below.
...	Arguments to be passed to mle

Details

Distributions available:

• Gamma: model = "gamma" or "g"

• Log-Normal: model = "lognorm" or "ln"

• Weibull: model = "weibull" or "w"

• Inverse Gaussian: model = "invgauss" or "ig"

Value

An object of class "ea".

Author(s)

[e-mail]

References

• Haas CN, Rose JB, Gerba CP (1999) Quantitative Microbial Risk Assessment. John Wiley & Sons, Inc.

See Also

ea_count, for modelling exposure from count data
ea_presence, for modelling exposure from presence/absence data

Examples

ea_conc(x = x, d = d, data = giardia, model = "weibull")

brechtdv/QMRA documentation built on May 13, 2019, 5:06 a.m.