View source: R/utils-singlediff-stationary.R
util_singlediff_ts | R Documentation |
This function attempts to make a non-stationary time series stationary by applying single differencing. It iteratively increases the differencing order until stationarity is achieved.
util_singlediff_ts(.time_series)
.time_series |
A time series object to be made stationary. |
The function calculates the frequency of the input time series using the stats::frequency
function.
It then applies single differencing incrementally until the Augmented Dickey-Fuller test indicates
stationarity (p-value < 0.05) or until the differencing order reaches the frequency of the data.
If single differencing successfully makes the time series stationary, it returns the stationary time series and related information as a list with the following elements:
stationary_ts: The stationary time series after differencing.
ndiffs: The order of differencing applied to make it stationary.
adf_stats: Augmented Dickey-Fuller test statistics on the stationary time series.
trans_type: Transformation type, which is "diff" in this case.
ret: TRUE to indicate a successful transformation.
If the data requires more single differencing than its frequency allows, it informs the user and returns a list with ret set to FALSE, indicating that double differencing may be needed.
If the time series is already stationary or the single differencing is successful, it returns a list as described in the details section. If additional differencing is required, it informs the user and returns a list with ret set to FALSE.
Steven P. Sanderson II, MPH
Other Utility:
auto_stationarize()
,
calibrate_and_plot()
,
internal_ts_backward_event_tbl()
,
internal_ts_both_event_tbl()
,
internal_ts_forward_event_tbl()
,
model_extraction_helper()
,
ts_get_date_columns()
,
ts_info_tbl()
,
ts_is_date_class()
,
ts_lag_correlation()
,
ts_model_auto_tune()
,
ts_model_compare()
,
ts_model_rank_tbl()
,
ts_model_spec_tune_template()
,
ts_qq_plot()
,
ts_scedacity_scatter_plot()
,
ts_to_tbl()
,
util_difflog_ts()
,
util_doublediff_ts()
,
util_doubledifflog_ts()
,
util_log_ts()
# Example 1: Using a time series dataset
util_singlediff_ts(AirPassengers)
# Example 2: Using a different time series dataset
util_singlediff_ts(BJsales)$ret
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