DistrCollection {r6qualitytools} | R Documentation |
DistrCollection-class: Class 'DistrCollection'
Description
R6 Class for Managing a Collection of Distribution Objects
Public fields
distr
List of
Distr
objects.
Methods
Public methods
Method new()
Initialize the fields of the DistrCollection
object.
Usage
DistrCollection$new()
Method add()
Add a Distr
object to the collection.
Usage
DistrCollection$add(distr)
Arguments
distr
A
Distr
object to add to the collection.
Method get()
Get a Distr
object from the collection by its index.
Usage
DistrCollection$get(i)
Arguments
i
Integer index of the
Distr
object to retrieve.
Returns
A Distr
object.
Method print()
Print the summary of all distributions in the collection.
Usage
DistrCollection$print()
Method summary()
Summarize the goodness of fit for all distributions in the collection.
Usage
DistrCollection$summary()
Returns
A data frame with distribution names, Anderson-Darling test statistics, and p-values.
Method plot()
Plot all distributions in the collection.
Usage
DistrCollection$plot( xlab = NULL, ylab = NULL, xlim = NULL, ylim = NULL, line.col = "red", fill.col = "lightblue", border.col = "black", line.width = 1, box = TRUE )
Arguments
xlab
Character string for the x-axis label.
ylab
Character string for the y-axis label.
xlim
Numeric vector specifying the x-axis limits.
ylim
Numeric vector specifying the y-axis limits.
line.col
Character string for the color of the plot line. Default is "red".
fill.col
Character string for the color of the histogram fill. Default is "lightblue".
border.col
Character string for the color of the histogram border. Default is "black".
line.width
Numeric value specifying the width of the plot line. Default is 1.
box
Logical value indicating whether to draw a box with the parameters in the plot. Default is TRUE.
Method clone()
The objects of this class are cloneable with this method.
Usage
DistrCollection$clone(deep = FALSE)
Arguments
deep
Whether to make a deep clone.
See Also
Examples
set.seed(123)
data1 <- rnorm(100, mean = 5, sd = 2)
parameters1 <- list(mean = 5, sd = 2)
distr1 <- Distr$new(x = data1, name = "normal",
parameters = parameters1, sd = 2,
n = 100, loglik = -120)
data2 <- rpois(100, lambda = 3)
parameters2 <- list(lambda = 3)
distr2 <- Distr$new(x = data2, name = "poisson",
parameters = parameters2, sd = sqrt(3),
n = 100, loglik = -150)
collection <- DistrCollection$new()
collection$add(distr1)
collection$add(distr2)
collection$summary()
collection$plot()