fastcpd_var() and fastcpd.var() are
wrapper functions of fastcpd_ts() to find change points in
VAR(\(p\)) models. The function is similar to fastcpd_ts()
except that the data is by default a matrix with row as an observation
and thus a formula is not required here.
Arguments
- data
A matrix, a data frame or a time series object.
- order
A positive integer specifying the order of the VAR model.
- ...
Other arguments passed to
fastcpd(), for example,segment_count.
Value
A fastcpd object.
Examples
set.seed(1)
n <- 300
p <- 2
theta_1 <- matrix(c(-0.3, 0.6, -0.5, 0.4, 0.2, 0.2, 0.2, -0.2), nrow = p)
theta_2 <- matrix(c(0.3, -0.4, 0.1, -0.5, -0.5, -0.2, -0.5, 0.2), nrow = p)
x <- matrix(0, n + 2, p)
for (i in 1:200) {
x[i + 2, ] <- theta_1 %*% c(x[i + 1, ], x[i, ]) + rnorm(p, 0, 1)
}
for (i in 201:n) {
x[i + 2, ] <- theta_2 %*% c(x[i + 1, ], x[i, ]) + rnorm(p, 0, 1)
}
result <- fastcpd.var(x, 2)
#> Warning: argument is not a function
summary(result)
#>
#> Call:
#> fastcpd.var(data = x, order = 2)
#>
#> Change points:
#> 204
#>
#> Cost values:
#> 583.9159 306.6093
#>
#> Parameters:
#> segment 1 segment 2
#> 1 -0.2524511 0.2760795
#> 2 -0.5679217 0.2764738
#> 3 0.2065672 -0.5327953
#> 4 0.2451136 -0.4303701
#> 5 0.5655444 -0.3844917
#> 6 0.3903103 -0.5302748
#> 7 0.1614109 -0.1918981
#> 8 -0.1716114 0.1671678