adam_params: Tuning Parameters for ADAM Models

adam_paramsR Documentation

Tuning Parameters for ADAM Models

Description

Tuning Parameters for ADAM Models

Usage

use_constant(values = c(FALSE, TRUE))

regressors_treatment(values = c("use", "select", "adapt"))

outliers_treatment(values = c("ignore", "use", "select"))

probability_model(
  values = c("none", "auto", "fixed", "general", "odds-ratio", "inverse-odds-ratio",
    "direct")
)

distribution(
  values = c("default", "dnorm", "dlaplace", "ds", "dgnorm", "dlnorm", "dinvgauss",
    "dgamma")
)

information_criteria(values = c("AICc", "AIC", "BICc", "BIC"))

select_order(values = c(FALSE, TRUE))

Arguments

values

A character string of possible values.

Details

The main parameters for ADAM 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.

  • use_constant: Logical, determining, whether the constant is needed in the model or not.

  • regressors_treatment: The variable defines what to do with the provided explanatory variables.

  • outliers_treatment: Defines what to do with outliers.

  • probability_model: The type of model used in probability estimation.

  • distribution: What density function to assume for the error term.

  • information_criteria: The information criterion to use in the model selection / combination procedure.

  • select_order: If TRUE, then the function will select the most appropriate order.

Value

A dials parameter

A parameter

A parameter

A parameter

A parameter

A parameter

A parameter

A parameter

Examples

use_constant()

regressors_treatment()

distribution()



modeltime documentation built on Nov. 16, 2022, 5:09 p.m.