CalcThemAll.PRM (version 1.1.1)

Log_Logistic_Log_Logistic_Formula: Log Logistic Log Logistic (double curve) CDF Formula

Description

Log Logistic Log Logistic (double curve) CDF Formula

Usage

Log_Logistic_Log_Logistic_Formula(
  concentration,
  scale,
  shape_location,
  scale_2,
  shape_location_2,
  weight
)

Value

a numeric vector

Arguments

concentration

The vector of concentration values for a selected pesticide, that has a Log Logistic Log Logistic shaped species sensitivity distribution, to run the equation on.

scale

The alpha/scale value for the first Log Logistic equation for the selected pesticide. These can be found in the "pesticide_info" data frame provided in this package. If you are including other pesticides you will need to append them with their respective distribution variables to the "pesticide_info" table.

shape_location

The beta/shape value for the first Log Logistic equation for the selected pesticide. These can be found in the "pesticide_info" data frame provided in this package. If you are including other pesticides you will need to append them with their respective distribution variables to the "pesticide_info" table.

scale_2

The alpha/scale value for the second Log Logistic equation for the selected pesticide. These can be found in the "pesticide_info" data frame provided in this package. If you are including other pesticides you will need to append them with their respective distribution variables to the "pesticide_info" table.

shape_location_2

The beta/shape value for the second Log Logistic equation for the selected pesticide. These can be found in the "pesticide_info" data frame provided in this package. If you are including other pesticides you will need to append them with their respective distribution variables to the "pesticide_info" table.

weight

The weight parameter for combining the two equations for the selected pesticide. These can be found in the "pesticide_info" data frame provided in this package. If you are including other pesticides you will need to append them with their respective distribution variables to the "pesticide_info" table.

Examples

#This Example should produce roughly 1% and 5% PRM values
LogL_LogL_pesticide_concentrations <- c(0.00341453, 0.009854566)
Log_Logistic_Log_Logistic_Formula(concentration = LogL_LogL_pesticide_concentrations,
scale = 0.5823392, shape_location = -3.499604, scale_2 = 1.144555,
shape_location_2 = 1.100755, weight = 0.3585467)