smile.timeseries
Time series analysis and forecasting.
Attributes
Members list
Value members
Concrete methods
Auto-correlation function.
Auto-correlation function.
Value parameters
- lag
-
the lag.
- x
-
time series.
Attributes
- Returns
-
the auto-correlation.
Fits an autoregressive model AR(p).
Fits an autoregressive model AR(p).
Value parameters
- p
-
the order of AR.
- x
-
the time series.
Attributes
- Returns
-
the fitted model.
Fits an autoregressive integrated moving average model ARIMA(p, d, q).
Fits an autoregressive integrated moving average model ARIMA(p, d, q).
Value parameters
- d
-
the degree of differencing.
- p
-
the order of AR.
- q
-
the order of MA.
- x
-
the time series.
Attributes
- Returns
-
the fitted model.
Fits an autoregressive moving average model ARMA(p, q).
Fits an autoregressive moving average model ARMA(p, q).
Value parameters
- p
-
the order of AR.
- q
-
the order of MA.
- x
-
the time series.
Attributes
- Returns
-
the fitted model.
Box-Pierce test for serial correlation.
Box-Pierce test for serial correlation.
Value parameters
- lag
-
the maximum lag for the test.
- x
-
time series.
Attributes
- Returns
-
the test result.
Auto-covariance function.
Auto-covariance function.
Value parameters
- lag
-
the lag.
- x
-
time series.
Attributes
- Returns
-
the auto-covariance.
Computes the differencing of a time series.
Computes the differencing of a time series.
Value parameters
- differences
-
the order of differencing.
- lag
-
the lag at which to difference.
- x
-
time series.
Attributes
- Returns
-
the differenced series.
Computes the intermediate differencing stages of a time series.
Computes the intermediate differencing stages of a time series.
Value parameters
- differences
-
the order of differencing.
- lag
-
the lag at which to difference.
- x
-
time series.
Attributes
- Returns
-
the array of differencing stages.
Ljung-Box test for serial correlation.
Ljung-Box test for serial correlation.
Value parameters
- lag
-
the maximum lag for the test.
- x
-
time series.
Attributes
- Returns
-
the test result.
Partial auto-correlation function.
Partial auto-correlation function.
Value parameters
- lag
-
the lag.
- x
-
time series.
Attributes
- Returns
-
the partial auto-correlation.