multidata: Multidata Class

In iAR: Irregularly Observed Autoregressive Models

Multidata Class

Description

The 'multidata' class is an S7 class designed to represent multidimensional time series models, including the main time series and additional series (e.g., error standard deviations or related variables).

Usage

multidata(
  times = integer(0),
  series = integer(0),
  series_esd = integer(0),
  series_names = character(0)
)

Arguments

times	A numeric vector representing the time points of the time series.
series	A numeric vector or matrix representing the main time series.
series_esd	A numeric vector or matrix representing the additional series, such as error standard deviations or other related data.
series_names	An optional character vector representing the name of the series.

Validation Rules

- '@times' must be a numeric vector and strictly increasing. - '@series' must be a numeric matrix or empty. Its number of rows must match the length of '@times'. - '@series_esd' must be a numeric matrix or empty. If provided and not empty, its dimensions must match those of '@series'. - If '@series_names' is provided, it must be a character vector of the same length as the number of columns of '@series', and contain unique values.

See Also

[BiAR]

Examples

# Create a multidata object
multidata_instance <- multidata(
  times = c(1, 2, 3, 4),
  series = matrix(c(10, 20, 15, 25,
                    12, 18, 17, 23), 
                  nrow = 4, ncol = 2),
  series_esd = matrix(c(1, 1.5, 1.2, 1.8,
                        0.9, 1.3, 1.1, 1.7),
                      nrow = 4, ncol = 2)
)

iAR documentation built on Nov. 5, 2025, 6:19 p.m.