print.gfpop: print.gfpop

In gfpop: Graph-Constrained Functional Pruning Optimal Partitioning

print.gfpop

Description

Printing the resulting change-point model found by gfpop function

Usage

## S3 method for class 'gfpop'
print(x, ...)

Arguments

x	a gfpop class object
...	Other parameters

Value

print the gfpop object

Examples

n <- 1000 #data length
data <- dataGenerator(n, c(0.3, 0.4, 0.7, 0.95, 1), c(1, 3, 1, -1, 4), "mean", sigma = 3)
myGraph <- graph(type = "relevant", gap = 0.5, penalty = 2 * sdDiff(data) ^ 2 * log(n))
g <- gfpop(data, myGraph, type = "mean")
print(g)

gfpop documentation built on April 1, 2023, 12:22 a.m.