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Representation of regression in a matrix form: $$Y = XA + E,$$

where: $X$ - independent variables, $Y$ - dependent variables (observations), $E$ - errors, which have a uniform distribution, $A$ - regression parameter.

How to evaluate the parameters $A$ of this multivariate regression using the maximum likelihood method with a uniform distribution of errors?

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  • $\begingroup$ Is the range of the uniform distribution given or does it need to be estimated? What do you assume about the independence (or lack thereof) of $E$? $\endgroup$ – whuber May 27 '19 at 11:45
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    $\begingroup$ @whuber Thank you for the answer! Given: E = [e1, e2, ..., en] ’, // vector of residuals Where ei = U [-ui, ui]; The residuals ei have a uniform distribution with a known range [-ui, ui], All residuals are independent. I need to estimate the vector of parameters A and its variance. $\endgroup$ – Minh Đại May 27 '19 at 16:52

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