RE: AI-GEOSTATS: Unbaisedness
That’s what I was wondering unbiasedness is based on E(Z*) = the
mean,
But we know Z* is not the mean because we are estimating it. I'm sure
it's true, otherwise E(Z*-Z) = 0 would not be published so many books,
however there is not a lot of explanation of this assumption.
pp252 Practical Geostatistics 2000;
" ue = E{g1} - E{T} = u - u = 0 "
My question was how is does E{g1} = u, when we know it's value is g1.
Is this unbiasedness an assumption or a reality? An assumption so that
we only have to minimise, the variance, assuming the error distribution
has a zero mean.
Prof. Dr. K. Gerald v.d. Boogaart
sum_i w_i E[Z(x_i)] - E[Z(x_0)] =0
But how do you get here:
>
>
sumwu - u =0 says all Z(x) =u this is
> not true?
Re: AI-GEOSTATS: Unbaisedness
No, average of (Z*-Z) is zero average of (sum wZi - Z i)s zero sum wi times average of Z - average if Z =0 if sum w = 1 then this is true, otherwise not Says nothing at all about the average of Z. OK? IsobelDigby Millikan <[EMAIL PROTECTED]> wrote:BLUE : Best Linear Unbiased Estimator Best : Minimium error variance. Linear : Linear combination of sample values. Unbiased : E(Z*-Z) = 0 Estimator: An estimate Is unbiasedness a fas? E(Z*-Z) = 0 E(sumwZ(x) Z) = 0 sumwu u =0 says all Z(x) =u this is not true?
AI-GEOSTATS: Unbaisedness
BLUE : “Best Linear Unbiased Estimator” Best : Minimium error variance. Linear : Linear combination of sample values. Unbiased : E(Z*-Z) = 0 Estimator: An estimate Is unbiasedness a fas? E(Z*-Z) = 0 E(sumwZ(x) – Z) = 0 sumwu – u =0 says all Z(x) =u this is not true?
