pcSA-class: An S4 class to return the results of sensitivity analyses

In JohnNay/sa: Sensitivity Analysis for Complex Computational Models

Description

An S4 class to return the results of sensitivity analyses

Show

Plots pcSA S4 object, a Partial Correlation Analysis of a Simulation Model

Usage

## S4 method for signature 'pcSA'
print(x, ...)

## S4 method for signature 'pcSA'
show(object)

## S4 method for signature 'pcSA'
plot(x, outcome_var = "Outcome", xlab = "Variable",
  ylab = "Standardized Rank Regression Coefficient")

Arguments

x	The result slot of an object created by pc_sa.
...	ignored @export
object	S4 pcSA object @export
outcome_var	Optional character vector for labeling the outcome variable in the plot. Default is "Outcome".
xlab	Optional character vector for labeling the variables.
ylab	Optional character vector. Default is "Partial Rank Correlation Coefficient". Could also be "Partial Correlation Coefficient", "Standardized Rank Regression Coefficient", and "Standardized Regression Coefficient".

Value

Returns a ggplot2 plot.

Methods (by generic)

• print: An S4 method for printing a pcSA S4 object

• show: An S4 method for showing a pcSA S4 object

• plot: This is function of the eat package. pc_sa conducts a a partial correlation analysis.

Slots

call

Language from the call of the function.

input_set

data.frame of input set used

sims

numeric vector with outcome of simulating model with input_set

result

c("src", "pcc") s3 classes from sensitivity package.

r_squared

Numeric vector length one.

rmse

Numeric vector length one.

timing

Numeric vector length one with the total elapsed time it took to execute.

session

the results from calling sessionInfo() at end of pc_sa function.

References

J. C. Thiele, W. Kurth, V. Grimm, Facilitating Parameter Estimation and Sensitivity Analysis of Agent-Based Models: A Cookbook Using NetLogo and R. Journal of Artificial Societies and Social Simulation. 17, 11 (2014).

Examples

fake_abm <- function(params, out) {
  x1 <- params[1]
  x2 <- params[2]
  if (out=="sq") return(x1^2 + x2 + rnorm(1, 0))
  if (out=="ident") return(x1 + x2 + rnorm(1, 0))
}
inputs <- lapply(list(param1 = NA, param2 = NA), 
                 function(x) list(random_function = "qunif",
                                  ARGS = list(min = 0, max = 1)))
s <- pc_sa(fake_abm, inputs, "sq")
plot(s)

JohnNay/sa documentation built on May 7, 2019, 12:01 p.m.