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  1. K

    Bonferroni

    Yes Thanks David.
  2. K

    Heteroskedasticity?

    Hi Shakti, What does BP stands for? Also what i understood for homosked is that the error terms show constant variance. Are we saying there is a correlation between these error terms and the regressor under our consideration? And this being an assumption of least squares.
  3. K

    Bonferroni

    Hi David/Nicole, Is Bonferroni test important from the FRM exam point of view? Can't i skip it as i am really not getting the nag of it?
  4. K

    Weighted least squares estimator

    Thanks David. I feel my concepts are not very clear here which is why i am unable to connect the dots. According to my understanding errors are nothing but the difference between actual (Y) and predicted (Y^) independent variable. Homosked - is when errors have a constant variance so are we...
  5. K

    Weighted least squares estimator

    weighted least squares (WLS) estimator: If the errors are heteroskedastic, then OLS is no longer BLUE. If the heteroskedasticity is known (i.e., if the conditional variance of given is known up to a constant factor of proportionality) then an alternate estimator exists with a smaller variance...
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