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Methods for objects of type "SimTest", used to test a value against its distribution under a simulated null hypothesis.

Usage

as.SimTest(RealValue, SimulatedValues)
is.SimTest(x)
# S3 method for class 'SimTest'
autoplot(object, Quantiles = c(0.025, 0.975), ...,
  colValue = "red", colQuantiles = "black", ltyQuantiles = 2,
  main = NULL, xlab = "Simulated Values", ylab = "Density")
# S3 method for class 'SimTest'
plot(x, Quantiles = c(0.025, 0.975), ...,
  colValue = "red", lwdValue = 2, ltyValue = 2,
  colQuantiles = "black", lwdQuantiles = 1, ltyQuantiles = 2,
  main = NULL, xlab = "Simulated Values", ylab = "Density")
# S3 method for class 'SimTest'
summary(object, Quantiles = c(0.025, 0.975), ...)

Arguments

x

An object to be tested or plotted.

object

An object.

RealValue

A numeric Value (the actual one).

SimulatedValues

A numeric vector containing the simulated values.

Quantiles

A vector containing the quantiles of interest.

colValue

The color of the line representing the real value on the plot.

lwdValue

The width of the line representing the real value on the plot.

ltyValue

The line type of the line representing the real value on the plot.

colQuantiles

The color of the lines representing the quantiles on the plot.

lwdQuantiles

The width of the lines representing the quantiles on the plot.

ltyQuantiles

The line type of the lines representing the quantiles on the plot.

main

The main title of the plot. if NULL (by default), there is no title.

xlab

The X axis label.

ylab

The Y axis label.

...

Additional arguments to be passed to the generic methods.

Details

Simulated values should be obtained by simulation. The actual value is compared to simulated quantiles. SimTest objects can be plotted and summarized.

Value

SimTest objects are lists containing:

RealValue

The value to test.

SimulatedValues

A vector of simulated values, whose quantiles will be used for the test.

is.SimTest returns TRUE if the object is of class SimTest.

summary.SimTest returns a summary of the object, including the empirical quantile of the real value in the simulated distributon.

Examples

# Set the value to test
Real <- 0.8
# Is it a realization of a Gaussian distribution?
Sims <- rnorm(1000)
# Make a Simtest object
st <- as.SimTest(Real, Sims)
summary(st)
#> Real value:  0.8 
#> Quantile in the simulated distribution:  0.782 
#> Quantiles of simulations:
#> 2.50% :  -2.140066 
#> 97.50% :  2.177345 
#> Mean simulated value:  0.006135806 
# Plot
plot(st)

# ggplot
autoplot(st)