Time-series data generation wrapper function

data_gen() is a wrapper function for various time-series data generation methods. This is used to call one of six methods that generates data in the structure required for simulations for HBEST() or HBEST_fast().

Usage

gen_data(gen_method, ...)

Arguments

gen_method

Method of data generation to use. Options include ARp, AR1vary, AR2mix, MA4, MA4vary, and MA4varyType2.

...

further arguments, passed to chosen method. See details below.

Value

returns the appropriate objects based on the method chosen. See help pages for each function for more details.

Details

Available data generation methods include:

ARp	calls the generate_AR() function which is based on stats::arima.sim.
AR1vary	calls the generate_AR1_vary() function which is based on stats::arima.sim.
AR2mix	calls the generate_AR2_mixture() function which is based on stats::arima.sim and (Granados-Garcia et al. 2022) .
MA4	calls the generate_MA4() function which is based on stats::arima.sim.
MA4vary	calls the generate_MA4_vary() function which is based on stats::arima.sim.
MA4varyType2	calls the generate_MA4_varyType2() function which is based on stats::arima.sim.

Examples

## Other examples can be found in the vignette `Data_generation_tutorial`
R <- 20
n <- rep(500, R)
burn <- 50

## `ARp` method:
ts <- gen_data(
  gen_method = "ARp",
  phi = c(0.5),
  n = n,
  R = R,
  burn = burn
)

## `AR1vary` method:
ts <- gen_data(
  gen_method = "AR1vary",
  n = n,
  R = 5,
  min = 0.45,
  max = 0.6,
  burn = burn
)

## `AR2mix` method:
R <- 20
n <- c(rep(300, 10),
       rep(800, 10)
  )
peaks1 <- runif(R, min = 0.2, max = 0.23)
bandwidths1 <- runif(R, min = .1, max = .2)
peaks2 <- runif(R,
                min = (pi * (2 / 5)) - 0.1,
                max = (pi * (2 / 5)) + 0.1)
bandwidths2 <- rep(0.15, R)
peaks <- rbind(peaks1, peaks2)
bandwidths <- rbind(bandwidths1, bandwidths2)
ts <- gen_data(
  gen_method = "AR2mix",
  peaks = peaks,
  bandwidths = bandwidths,
  n = n
)

## `MA4` method:
n <- rep(500, R)
ts <- gen_data(
  gen_method = "MA4",
  n = n,
  R = R,
  burn = burn
)

## `MA4vary` method:
n <- rep(500, R)
alpha <- 0.05
ts <- gen_data(
  gen_method = "MA4vary",
  n = n,
  R = R,
  burn = burn,
  alpha = alpha
)

## `MA4varyType2` method:
n <- rep(500, R)
ts <- gen_data(
  gen_method = "MA4varyType2",
  n = n,
  R = R,
  burn = burn,
  alpha = alpha
)