
General Interface for "Support Vector Machine" ARIMA Regression Models
arima_svm_laplace.Rd
arima_svm_laplace()
is a way to generate a specification of a time series model
that uses SVMs to improve modeling errors (residuals) on Exogenous Regressors.
It works with both "automated" ARIMA (auto.arima
) and standard ARIMA (arima
).
The main algorithms are:
Auto ARIMA + SVM Errors (engine =
auto_arima_svm_laplace
, default)ARIMA + SVM Errors (engine =
arima_svm_laplace
)
Usage
arima_svm_laplace(
mode = "regression",
seasonal_period = NULL,
non_seasonal_ar = NULL,
non_seasonal_differences = NULL,
non_seasonal_ma = NULL,
seasonal_ar = NULL,
seasonal_differences = NULL,
seasonal_ma = NULL,
cost = NULL,
margin = NULL,
laplace_sigma = NULL
)
Arguments
- mode
A single character string for the type of model. The only possible value for this model is "regression".
- seasonal_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. See Fit Details below.
- non_seasonal_ar
The order of the non-seasonal auto-regressive (AR) terms. Often denoted "p" in pdq-notation.
- non_seasonal_differences
The order of integration for non-seasonal differencing. Often denoted "d" in pdq-notation.
- non_seasonal_ma
The order of the non-seasonal moving average (MA) terms. Often denoted "q" in pdq-notation.
- seasonal_ar
The order of the seasonal auto-regressive (SAR) terms. Often denoted "P" in PDQ-notation.
- seasonal_differences
The order of integration for seasonal differencing. Often denoted "D" in PDQ-notation.
- seasonal_ma
The order of the seasonal moving average (SMA) terms. Often denoted "Q" in PDQ-notation.
- cost
A positive number for the cost of predicting a sample within or on the wrong side of the margin
- margin
A positive number for the epsilon in the SVM insensitive loss function (regression only)
- laplace_sigma
sigma parameter for laplacian
- sample_size
number for the number (or proportion) of data that is exposed to the fitting routine.