bbo|ker @end|ng |rom gm@||@com
Tue Jul 2 13:30:04 CEST 2019
I'm not sure I understand all the details of your modeling framework,
but in general it's dangerous to compare REML for models with differing
fixed effects (which would probably? also include models with different
types of differencing). It might help if you provided some more
background (what is REMLP, is 'lmermod' a function or a package, what
is LDV, ... ?)
On 2019-07-01 6:34 p.m., S.D. Silver wrote:
> I am working with an r code procedure for a ARFIMA mutilevel model that
> estimates a
> linear mixed model fit by REMLP['lmermod']. I have now been asked to
> compare the model's results with alternatives that include ARFIMA-LDV.
> The only output diagnostics that the code provides in addition to
> parameter estimates is shown below :
> " REML criterion at convergence: 1694929 Scaled residuals:
> Min 1Q Median 3Q Max -3.4407 -0.7361 0.0482 0.7791 2.9853
> Random effects: Groups Name Variance Std.Dev. time
> (Intercept) 42.5 6.519 Residual 1229.0 35.057 Number of
> obs: 170217, groups: time, 363"
> I understand that REML is most directly about estimatingvariance
> components, but is it meaningful to consider it
> as a measure of fit in comparing nested models. Here the alternatives
> are LDV and an MLM that is not fractionally differenced.
> Given the difference in estimation methodology, I do not think it is
> feasible to compare 'lmermod' with alternatives in OLS.Do any comparable
> model variants for comparison in the estimation procedure of lme4 come
> to mind ?
> Would be grateful for any observations that you could provide.
> R-sig-mixed-models using r-project.org mailing list
More information about the R-sig-mixed-models