Hello, running a mixed model in the package LME4, lmer()
Panel data, have about 322 time periods and 50 states, total data set is
approx 15K records and about 20 explanatory variables. Not a very
large data set.
We run random intercepts as well as random coefficients for about 10 of
the variables, the rest come in as fixed effects. We are running into
a wall of time to execute these models.
A sample specification of all random effects:
lmer(Y ~ 1 + (x_078 + x_079 + growth_st_index +
retail_st_index + Natl + econ_home_st_index +
econ_bankruptcy + index2_HO + GPND_ST | state),
data = newData, doFit = TRUE)
Computation time is near 15 minutes.
System ELAPSED User
21.4 888.63 701.74
Does anyone have any ideas on way's to speed up lmer(), as well any
parallel implementations, or approaches/options to reduce computation time?
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