adam_fit_impl: Low-Level ADAM function for translating modeltime to forecast

View source: R/parsnip-adam.R

adam_fit_implR Documentation

Low-Level ADAM function for translating modeltime to forecast

Description

Low-Level ADAM function for translating modeltime to forecast

Usage

adam_fit_impl(
  x,
  y,
  period = "auto",
  p = 0,
  d = 0,
  q = 0,
  P = 0,
  D = 0,
  Q = 0,
  model = "ZXZ",
  constant = FALSE,
  regressors = c("use", "select", "adapt"),
  outliers = c("ignore", "use", "select"),
  level = 0.99,
  occurrence = c("none", "auto", "fixed", "general", "odds-ratio", "inverse-odds-ratio",
    "direct"),
  distribution = c("default", "dnorm", "dlaplace", "ds", "dgnorm", "dlnorm", "dinvgauss",
    "dgamma"),
  loss = c("likelihood", "MSE", "MAE", "HAM", "LASSO", "RIDGE", "MSEh", "TMSE", "GTMSE",
    "MSCE"),
  ic = c("AICc", "AIC", "BIC", "BICc"),
  select_order = FALSE,
  ...
)

Arguments

x

A data.frame of predictors

y

A vector with outcome

period

A seasonal frequency. Uses "auto" by default. A character phrase of "auto" or time-based phrase of "2 weeks" can be used if a date or date-time variable is provided.

p

The order of the non-seasonal auto-regressive (AR) terms. Often denoted "p" in pdq-notation.

d

The order of integration for non-seasonal differencing. Often denoted "d" in pdq-notation.

q

The order of the non-seasonal moving average (MA) terms. Often denoted "q" in pdq-notation.

P

The order of the seasonal auto-regressive (SAR) terms. Often denoted "P" in PDQ-notation.

D

The order of integration for seasonal differencing. Often denoted "D" in PDQ-notation.

Q

The order of the seasonal moving average (SMA) terms. Often denoted "Q" in PDQ-notation.

model

The type of ETS model.

constant

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

regressors

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

outliers

Defines what to do with outliers.

level

What confidence level to use for detection of outliers.

occurrence

The type of model used in probability estimation.

distribution

what density function to assume for the error term.

loss

The type of Loss Function used in optimization.

ic

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

select_order

If TRUE, then the function will select the most appropriate order using a mechanism similar to auto.msarima(), but implemented in auto.adam(). The values list(ar=...,i=...,ma=...) specify the maximum orders to check in this case

...

Additional arguments passed to smooth::adam


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