Plot an automatic seasonal-analysis result

Provides a compact default plot for the main result class returned by auto_seasonal_analysis(). The plot is intended for quick inspection; the HTML report remains the richer review artifact.

Usage

# S3 method for class 'auto_seasonal_analysis'
plot(
  x,
  series = c("final", "seasonal", "original"),
  xlab = "time",
  ylab = NULL,
  ...
)

Arguments

x

An object returned by auto_seasonal_analysis().

series

Which series to show. "final" plots the selected seasonally adjusted series when available and falls back to the original series for do-not-adjust cases. "seasonal" plots the selected seasonal component when available. "original" plots the original input series stored in the result.

xlab, ylab

Axis labels.

...

Additional arguments passed to stats::plot.ts().

Value

Invisibly, x.

Examples

# \donttest{
if (requireNamespace("seasonal", quietly = TRUE)) {
  res <- auto_seasonal_analysis(AirPassengers, max_specs = 3)
  plot(res)
}
#> Model used in SEATS is different: (1 1 2)(1 0 0)
#> Model used in SEATS is different: (1 1 2)(1 0 0)
#> Model used in SEATS is different: (1 1 1)(1 0 0)
#> seas(
#>   x = structure(c(112, 118, 132, 129, 121, 135, 148, 148, 136, 119, 104, 118, 115, 126, 141, 135, 125, 149, 170, 170, 158, 133, 114, 140, 145, 150, 178, 163, 172, 178, 199, 199, 184, 162, 146, 166, 171, 180, 193, 181, 183, 218, 230, 242, 209, 191, 172, 194, 196, 196, 236, 235, 229, 243, 264, 272, 237, 211, 180, 201, 204, 188, 235, 227, 234, 264, 302, 293, 259, 229, 203, 229, 242, 233, 267, 269, 270, 315, 364, 347, 312, 274, 237, 278, 284, 277, 317, 313, 318, 374, 413, 405, 355, 306, 271, 306, 315, 301,  356, 348, 355, 422, 465, 467, 404, 347, 305, 336, 340, 318, 362, 348, 363, 435, 491, 505, 404, 359, 310, 337, 360, 342, 406, 396, 420, 472, 548, 559, 463, 407, 362, 405, 417, 391, 419, 461, 472, 535, 622, 606, 508, 461, 390, 432), tsp = c(1949, 1960.91666666667, 12), class = "ts"),
#>   seats.noadmiss = "no",
#>   transform.function = "log",
#>   arima.model = "(0 1 0)(0 1 1)",
#>   seats = "",
#>   regression.variables = "easter[8]",
#>   regression.aictest = NULL,
#>   outlier = NULL
#> )
#> seas(
#>   x = structure(c(112, 118, 132, 129, 121, 135, 148, 148, 136, 119, 104, 118, 115, 126, 141, 135, 125, 149, 170, 170, 158, 133, 114, 140, 145, 150, 178, 163, 172, 178, 199, 199, 184, 162, 146, 166, 171, 180, 193, 181, 183, 218, 230, 242, 209, 191, 172, 194, 196, 196, 236, 235, 229, 243, 264, 272, 237, 211, 180, 201, 204, 188, 235, 227, 234, 264, 302, 293, 259, 229, 203, 229, 242, 233, 267, 269, 270, 315, 364, 347, 312, 274, 237, 278, 284, 277, 317, 313, 318, 374, 413, 405, 355, 306, 271, 306, 315, 301,  356, 348, 355, 422, 465, 467, 404, 347, 305, 336, 340, 318, 362, 348, 363, 435, 491, 505, 404, 359, 310, 337, 360, 342, 406, 396, 420, 472, 548, 559, 463, 407, 362, 405, 417, 391, 419, 461, 472, 535, 622, 606, 508, 461, 390, 432), tsp = c(1949, 1960.91666666667, 12), class = "ts"),
#>   seats.noadmiss = "no",
#>   transform.function = "log",
#>   arima.model = "(0 1 0)(0 1 1)",
#>   seats = "",
#>   regression.variables = "easter[8]",
#>   regression.aictest = NULL,
#>   outlier = NULL
#> )
#> seas(
#>   x = structure(c(112, 118, 132, 129, 121, 135, 148, 148, 136, 119, 104, 118, 115, 126, 141, 135, 125, 149, 170, 170, 158, 133, 114, 140, 145, 150, 178, 163, 172, 178, 199, 199, 184, 162, 146, 166, 171, 180, 193, 181, 183, 218, 230, 242, 209, 191, 172, 194, 196, 196, 236, 235, 229, 243, 264, 272, 237, 211, 180, 201, 204, 188, 235, 227, 234, 264, 302, 293, 259, 229, 203, 229, 242, 233, 267, 269, 270, 315, 364, 347, 312, 274, 237, 278, 284, 277, 317, 313, 318, 374, 413, 405, 355, 306, 271, 306, 315, 301,  356, 348, 355, 422, 465, 467, 404, 347, 305, 336, 340, 318, 362, 348, 363, 435, 491, 505, 404, 359, 310, 337, 360, 342, 406, 396, 420, 472, 548, 559, 463, 407, 362, 405, 417, 391, 419, 461, 472, 535, 622, 606, 508, 461, 390, 432), tsp = c(1949, 1960.91666666667, 12), class = "ts"),
#>   seats.noadmiss = "no",
#>   transform.function = "log",
#>   arima.model = "(1 1 1)(0 1 1)",
#>   seats = "",
#>   regression.variables = "easter[8]",
#>   regression.aictest = NULL,
#>   outlier = NULL
#> )
#> seas(
#>   x = structure(c(112, 118, 132, 129, 121, 135, 148, 148, 136, 119, 104, 118, 115, 126, 141, 135, 125, 149, 170, 170, 158, 133, 114, 140, 145, 150, 178, 163, 172, 178, 199, 199, 184, 162, 146, 166, 171, 180, 193, 181, 183, 218, 230, 242, 209, 191, 172, 194, 196, 196, 236, 235, 229, 243, 264, 272, 237, 211, 180, 201, 204, 188, 235, 227, 234, 264, 302, 293, 259, 229, 203, 229, 242, 233, 267, 269, 270, 315, 364, 347, 312, 274, 237, 278, 284, 277, 317, 313, 318, 374, 413, 405, 355, 306, 271, 306, 315, 301,  356, 348, 355, 422, 465, 467, 404, 347, 305, 336, 340, 318, 362, 348, 363, 435, 491, 505, 404, 359, 310, 337, 360, 342, 406, 396, 420, 472, 548, 559, 463, 407, 362, 405, 417, 391, 419, 461, 472, 535, 622, 606, 508, 461, 390, 432), tsp = c(1949, 1960.91666666667, 12), class = "ts"),
#>   seats.noadmiss = "no",
#>   transform.function = "log",
#>   arima.model = "(1 1 1)(0 1 1)",
#>   seats = "",
#>   regression.variables = "easter[8]",
#>   regression.aictest = NULL,
#>   outlier = NULL
#> )
#> seas(
#>   x = structure(c(112, 118, 132, 129, 121, 135, 148, 148, 136, 119, 104, 118, 115, 126, 141, 135, 125, 149, 170, 170, 158, 133, 114, 140, 145, 150, 178, 163, 172, 178, 199, 199, 184, 162, 146, 166, 171, 180, 193, 181, 183, 218, 230, 242, 209, 191, 172, 194, 196, 196, 236, 235, 229, 243, 264, 272, 237, 211, 180, 201, 204, 188, 235, 227, 234, 264, 302, 293, 259, 229, 203, 229, 242, 233, 267, 269, 270, 315, 364, 347, 312, 274, 237, 278, 284, 277, 317, 313, 318, 374, 413, 405, 355, 306, 271, 306, 315, 301,  356, 348, 355, 422, 465, 467, 404, 347, 305, 336, 340, 318, 362, 348, 363, 435, 491, 505, 404, 359, 310, 337, 360, 342, 406, 396, 420, 472, 548, 559, 463, 407, 362, 405, 417, 391, 419, 461, 472, 535, 622, 606, 508, 461, 390, 432), tsp = c(1949, 1960.91666666667, 12), class = "ts"),
#>   seats.noadmiss = "no",
#>   transform.function = "log",
#>   arima.model = "(0 1 1)(0 1 1)",
#>   seats = "",
#>   regression.variables = "easter[1]",
#>   regression.aictest = NULL,
#>   outlier = NULL
#> )
#> seas(
#>   x = structure(c(112, 118, 132, 129, 121, 135, 148, 148, 136, 119, 104, 118, 115, 126, 141, 135, 125, 149, 170, 170, 158, 133, 114, 140, 145, 150, 178, 163, 172, 178, 199, 199, 184, 162, 146, 166, 171, 180, 193, 181, 183, 218, 230, 242, 209, 191, 172, 194, 196, 196, 236, 235, 229, 243, 264, 272, 237, 211, 180, 201, 204, 188, 235, 227, 234, 264, 302, 293, 259, 229, 203, 229, 242, 233, 267, 269, 270, 315, 364, 347, 312, 274, 237, 278, 284, 277, 317, 313, 318, 374, 413, 405, 355, 306, 271, 306, 315, 301,  356, 348, 355, 422, 465, 467, 404, 347, 305, 336, 340, 318, 362, 348, 363, 435, 491, 505, 404, 359, 310, 337, 360, 342, 406, 396, 420, 472, 548, 559, 463, 407, 362, 405, 417, 391, 419, 461, 472, 535, 622, 606, 508, 461, 390, 432), tsp = c(1949, 1960.91666666667, 12), class = "ts"),
#>   seats.noadmiss = "no",
#>   transform.function = "log",
#>   arima.model = "(0 1 1)(0 1 1)",
#>   seats = "",
#>   regression.variables = "easter[1]",
#>   regression.aictest = NULL,
#>   outlier = NULL
#> )

# }