If I have a simple model where Yi equals some constant plus an error term like Yi = B + Ei To minimize the SSE of this model, I would use the mean value of Y for B. How can I prove that the mean of Y minimizes the SSE?
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Originally Posted by DannyOcean If I have a simple model where Yi equals some constant plus an error term like Yi = B + Ei To minimize the SSE of this model, I would use the mean value of Y for B. How can I prove that the mean of Y minimizes the SSE? Let $\displaystyle x$ be our estimate of the value of $\displaystyle B$, then the SSE corresponding to x is: $\displaystyle SSE(x)=\sum_i (Y_i - x)^2$ differentiate and set to zero to find the $\displaystyle x$ that minimises $\displaystyle SSE(X)$. CB
Originally Posted by DannyOcean If I have a simple model where Yi equals some constant plus an error term like Yi = B + Ei To minimize the SSE of this model, I would use the mean value of Y for B. How can I prove that the mean of Y minimizes the SSE? Let $\displaystyle x$ be our estimate of the value of $\displaystyle B$, then the SSE corresponding to x is: $\displaystyle SSE(x)=\sum_i (Y_i - x)^2$ differentiate and set to zero to find the $\displaystyle x$ that minimises $\displaystyle SSE(x)$. CB
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