Find change points efficiently in variance change models

fastcpd_variance() and fastcpd.variance() are wrapper functions of fastcpd() to find the variance change. The function is similar to fastcpd() except that the data is by default a matrix or data frame or a vector with each row / element as an observation and thus a formula is not required here.

Usage

fastcpd_variance(data, ...)

fastcpd.variance(data, ...)

Arguments

data

A matrix, a data frame or a vector.

...

Other arguments passed to fastcpd(), for example, segment_count.

Value

A fastcpd object.

See also

fastcpd()

Examples

set.seed(1)
data <- c(rnorm(300, 0, 1), rnorm(400, 0, 10), rnorm(300, 0, 1))
system.time(result <- fastcpd.variance(data))
#> Warning: argument is not a function
#>    user  system elapsed 
#>   0.003   0.000   0.003 
summary(result)
#> 
#> Call:
#> fastcpd.variance(data = data)
#> 
#> Change points:
#> 300 700 
#> 
#> Cost values:
#> 1.341031 945.1872 30.94909 
#> 
#> Parameters:
#>   segment 1 segment 2 segment 3
#> 1 0.9287098  111.3079  1.159284
plot(result)

if (requireNamespace("mvtnorm", quietly = TRUE)) {
  set.seed(1)
  p <- 3
  data <- rbind(
    mvtnorm::rmvnorm(
      3e+5, rep(0, p), crossprod(matrix(runif(p^2) * 2 - 1, p))
    ),
    mvtnorm::rmvnorm(
      4e+5, rep(0, p), crossprod(matrix(runif(p^2) * 2 - 1, p))
    ),
    mvtnorm::rmvnorm(
      3e+5, rep(0, p), crossprod(matrix(runif(p^2) * 2 - 1, p))
    )
  )
  result_time <- system.time(
    result <- fastcpd.variance(data, r.progress = FALSE, cp_only = TRUE)
  )
  print(result_time)
  summary(result)
}
#> Warning: argument is not a function
#>    user  system elapsed 
#>   0.702   0.102   0.803 
#> 
#> Call:
#> fastcpd.variance(data = data, r.progress = FALSE, cp_only = TRUE)
#> 
#> Change points:
#> 300002 700003