Estimation

Fit regression model with ARIMA errors to data or estimate robust standard errors

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After specifying a time series regression model, use estimate to fit it to data. Infer the residuals for diagnostic checking using infer before simulating or forecasting. Alternatively, use fgls or hac to estimate FGLS coefficients and their standard errors or fit a linear regression model and estimate heteroscedasticity and autocorrelation consistent (HAC) coefficient standard errors, respectively.

Functions

estimate Estimate parameters of regression models with ARIMA errors
infer Infer innovations of regression models with ARIMA errors
print Display estimation results for regression models with ARIMA errors
arima Convert regression model with ARIMA errors to ARIMAX model
hac Heteroscedasticity and autocorrelation consistent covariance estimators
fgls Feasible generalized least squares
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