Tuning Parameters for SARIMA Models

non_seasonal_ar(range = c(0L, 5L), trans = NULL)

non_seasonal_differences(range = c(0L, 2L), trans = NULL)

non_seasonal_ma(range = c(0L, 5L), trans = NULL)

seasonal_ar(range = c(0L, 2L), trans = NULL)

seasonal_differences(range = c(0L, 1L), trans = NULL)

seasonal_ma(range = c(0L, 2L), trans = NULL)

markov_chains(range = c(0L, 8L), trans = NULL)

adapt_delta(range = c(0, 1), trans = NULL)

tree_depth(range = c(0L, 100L), trans = NULL)

Arguments

range	A two-element vector holding the defaults for the smallest and largest possible values, respectively.
trans	A `trans` object from the `scales` package, such as `scales::log10_trans()` or `scales::reciprocal_trans()`. If not provided, the default is used which matches the units used in `range`. If no transformation, `NULL`.

Value

A parameter

Details

The main parameters for SARIMA models are:

non_seasonal_ar: The order of the non-seasonal auto-regressive (AR) terms.
non_seasonal_differences: The order of integration for non-seasonal differencing.
non_seasonal_ma: The order of the non-seasonal moving average (MA) terms.
seasonal_ar: The order of the seasonal auto-regressive (SAR) terms.
seasonal_differences: The order of integration for seasonal differencing.
seasonal_ma: The order of the seasonal moving average (SMA) terms.
markov_chains: The number of markov chains.
adapt_delta: The thin of the jumps in a HMC method
tree_depth: Maximum depth of the trees

Examples

non_seasonal_ar()
#> Non-seasonal AR Term (quantitative)
#> Range: [0, 5]

non_seasonal_differences()
#> Non-seasonal Differencing Term (quantitative)
#> Range: [0, 2]

non_seasonal_ma()
#> Non-seasonal MA Term (quantitative)
#> Range: [0, 5]