R: Tidying methods for ARIMA modeling of time series

Arima_tidiers {broom} | 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'
    tidy(x, conf.int = FALSE, conf.level = 0.95, ...)

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

### Arguments

`x` | An object of class "Arima"
`conf.int` | whether to include a confidence interval
`conf.level` | confidence level of the interval, used only if `conf.int=TRUE`
`...` | extra arguments (not used)

### Details

`augment` is not currently implemented, as it is not clear whether ARIMA predictions can or should be merged with the original data frame.

### Value

All tidying methods return a data.frame without rownames, whose structure depends on the method chosen.

`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
`std.error` | The standard error from the linear model

If `conf.int = TRUE`, also returns

`conf.low` | low end of confidence interval
`conf.high` | high end of confidence interval

`glance` returns one row with the columns

`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

### See Also

arima

### Examples

    fit <- arima(lh, order = c(1, 0, 0))
    tidy(fit)
    glance(fit)

[Package broom version 0.4.2 Index]