[R-sig-ME] Need an advise on bias and MSE estimation
bbolker at gmail.com
Sun Jan 22 00:32:02 CET 2017
This question isn't really appropriate for this list, for a couple of
reasons: (1) it isn't about *mixed* models (which assume a continuous,
typically, Normal, mixture distribution rather than a discrete mixture
distribution); (2) it's pretty loosely related to R. While someone
*might* help you here out of the goodness of their heart, I'd say that
the best places to get help would be (1) if you're a student, from your
professor or a senior student/colleague at your institution; (2)
http://stats.stackexchange.com . If you ask in the latter place, it
would be good to reproduce the equations you're asking about in LaTeX
format within your question itself, to save people the trouble of
looking them up in the linked papers.
On 17-01-21 04:10 PM, jas ni wrote:
> Hi guys,
> I'm about to implement the comparison in my experimental work for missing
> data through EM algorithm using regression.
> I want to measure the bias and MSE on the parameters mean, beta1, beta2 and
> sigma and my current references are from this papers (page 206):
> I do confuse between m and j variables.
> I also refer to the attached paper and do confuse between t and j variables.
> Both papers presented to measure the bias. But both equations has different
> I could not implement the equation in R code because i do confuse with the
> variables for instance, m and j as shown in the equation in paper 1.
> I using the EM algorithm which is each iteration would produce the
> parameter mean, variance and beta. But the parameter estimation values
> would be generated based on the number of iteration but not based on the
> number of records or data points.
> If you could explain, why in the bias equation we need to sum the parameter
> values up to the number of data points. For example, i have the Old
> Faithful geyser dataset that contains 272 instances. Does it mean that i
> should generate the 272 estimated mean, variances and betas and sum all of
> them together?
> - J
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