View source: R/calculate_risk.R
calculate_risk | R Documentation |
This function calculates the expected risk measure for each policy alternative using the outputs from multiple model runs with different input parameter sets (e.g., probabilistic sensitivity, uncertainty, or Bayesian inference analysis).
calculate_risk(data, tmin, tmax, Dt, Dt_max = TRUE, W = FALSE, weight = NULL)
data |
A list of data.frames (one data.frame for each policy alternative). |
tmin |
A numeric value or a date specifying the minimum simulation time
to include in the analysis (ex. 1 or "2021-01-01"). This should correspond to a value in the first
column of each data.frame in |
tmax |
A numeric value or a date specifying the maximum simulation time to
include in the analysis (ex. 100 or "2021-04-10"). This should correspond to a value in the first
column of each data.frame in |
Dt |
A numeric vector of decision thresholds, one for each model
time step between |
Dt_max |
A logical value indicating whether the decision threshold
is a maximum ( |
W |
A logical value indicating whether the risk calculation should
be weighted ( |
weight |
A list of numeric vectors of weights for the risk calculation,
with one weight corresponding to each time step. Required if |
A list of risk scores, one for each policy alternative.
Each data.frame in data
contains the results from multiple model
runs using different parameter sets (e.g., from probabilistic sensitivity,
uncertainty, or Bayesian inference analysis). The first column contains
the model time and subsequent columns contain the predicted output for
each simulation run at the respective time.
The model time in the first column must contain numeric values indicating
a simulation time (ex. 1, 2, 3,...) or dates (ex. "2021-01-01", "2021-01-02")
which must be in R
Date format (i.e., class="Date"). To ensure a consistent
basis for comparison, the model time in the first column should be the same for
each policy alternative (data.frame).
tmin <- "2021-01-01"
tmax <- "2021-04-10"
Dt <- rep(750, nrow(psa_data$Baseline))
calculate_risk(
psa_data,
tmin = tmin,
tmax = tmax,
Dt = Dt,
Dt_max = TRUE
)
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