R: Tidying methods for ARIMA modeling of time series

tidiers_arima {sweep} | R Documentation

## Tidying methods for ARIMA modeling of time series

### Description

These methods tidy the coefficients of ARIMA models of univariate time series.

### Usage

    ## S3 method for class 'Arima'
    sw_tidy(x, ...)

    ## S3 method for class 'Arima'
    sw_glance(x, ...)

    ## S3 method for class 'Arima'
    sw_augment(x, data = NULL, rename_index = "index", timetk_idx = FALSE, ...)

    ## S3 method for class 'stlm'
    sw_tidy(x, ...)

### Arguments

`x` | An object of class "Arima"
`...` | Additional parameters (not used)
`data` | Used with `sw_augment` only. `NULL` by default which simply returns augmented columns only. User can supply the original data, which returns the data + augmented columns.
`rename_index` | Used with `sw_augment` only. A string representing the name of the index generated.
`timetk_idx` | Used with `sw_augment` only. Uses a irregular timetk index if present.

### Value

`sw_tidy()` returns one row for each coefficient in the model, with five columns:

- `term`: The term in the nonlinear model being estimated and tested

- `estimate`: The estimated coefficient

`sw_glance()` returns one row with the columns

- `model.desc`: A description of the model including the three integer components (p, d, q) are the AR order, the degree of differencing, and the MA order.

- `sigma`: The square root of the estimated residual variance

- `logLik`: The data's log-likelihood under the model

- `AIC`: The Akaike Information Criterion

- `BIC`: The Bayesian Information Criterion

- `ME`: Mean error

- `RMSE`: Root mean squared error

- `MAE`: Mean absolute error

- `MPE`: Mean percentage error

- `MAPE`: Mean absolute percentage error

- `MASE`: Mean absolute scaled error

- `ACF1`: Autocorrelation of errors at lag 1

`sw_augment()` returns a tibble with the following time series attributes:

- `index`: An index is either attempted to be extracted from the model or a sequential index is created for plotting purposes

- `.actual`: The original time series

- `.fitted`: The fitted values from the model

- `.resid`: The residual values from the model

`sw_tidy()` returns the underlying ETS or ARIMA model's `sw_tidy()` one row for each coefficient in the model, with five columns:

- `term`: The term in the nonlinear model being estimated and tested

- `estimate`: The estimated coefficient

### See Also

`arima()`, Arima()

### Examples

    library(dplyr)
    library(forecast)
    library(sweep)

    fit_arima <- WWWusage %>%
        auto.arima()

    sw_tidy(fit_arima)
    sw_glance(fit_arima)
    sw_augment(fit_arima)

[Package sweep version 0.2.3 Index]