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I am doing auto-regress by usual linear regression package.
e.g. $y_t=φx+ε_t$ with $x =y_{t-1}$

My reason is that,
Auto-regression does assumes iid errors, same for linear regression. Linear Regression doesn't have assumption on independent variables. What's different is merely that the independent variables is replaced with lagged dependent variable y.

But I see AR always is fitted by specific methods, I am afraid I'm doing wrong.

I am doing auto-regress by usual linear regression package.

My reason is that,
Auto-regression does assumes iid errors, same for linear regression. Linear Regression doesn't have assumption on independent variables. What's different is merely that the independent variables is replaced with lagged dependent variable y.

But I see AR always is fitted by specific methods, I am afraid I'm doing wrong.

I am doing auto-regress by usual linear regression package.
e.g. $y_t=φx+ε_t$ with $x =y_{t-1}$

My reason is that,
Auto-regression does assumes iid errors, same for linear regression. Linear Regression doesn't have assumption on independent variables. What's different is merely that the independent variables is replaced with lagged dependent variable y.

But I see AR always is fitted by specific methods, I am afraid I'm doing wrong.

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What's wrong if I fit the auto-regression with OLS?

I am doing auto-regress by usual linear regression package.

My reason is that,
Auto-regression does assumes iid errors, same for linear regression. Linear Regression doesn't have assumption on independent variables. What's different is merely that the independent variables is replaced with lagged dependent variable y.

But I see AR always is fitted by specific methods, I am afraid I'm doing wrong.