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))
Value
A dials
parameter
A parameter
A parameter
A parameter
A parameter
A parameter
A parameter
A parameter
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.
Examples
use_constant()
#> Warning: The `default` argument of `new_qual_param()` is deprecated as of dials 1.1.0.
#> ℹ The deprecated feature was likely used in the modeltime package.
#> Please report the issue at
#> <https://github.com/business-science/modeltime/issues>.
#> Logical, determining, whether the constant is needed in the model or not (qualitative)
#> 2 possible values include:
#> FALSE and TRUE
regressors_treatment()
#> The variable defines what to do with the provided explanatory variables. (qualitative)
#> 3 possible values include:
#> 'use', 'select' and 'adapt'
distribution()
#> What density function to assume for the error term. (qualitative)
#> 8 possible values include:
#> 'default', 'dnorm', 'dlaplace', 'ds', 'dgnorm', 'dlnorm', 'dinvgauss' and 'dg...