Solved:Fit an AR(1) to xt using maximum likelihood (basically unconditional least squares) as in Section 3.6. The easiest way to do this is to use sarima from astsa. Comment on the significance of the regression parameter estimates of the model. What is the estimate of the white noise variance.

 ARIMA models (including improved diagnostics) in a short command. It can also be used to perform regression with autocorrelated errors. This is a front end to arima () with a different back door.  

Usage Regression coefficients represent the mean change in the response variable for one unit of change in the predictor variable while holding other predictors in the model constant. .

Explanation: White noise refers to a statistical model for signals and signal sources, rather than to any specific signal. White noise draws its name from white light.

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