I have a function myFunction(beta,x) where beta is a vector of coefficients
and x is a data frame (think of it as a matrix). I want to optimize the
function myFunction() by ONLY changing beta, i.e. x stays constant, with 4
constraints. I have the following code (with a separate source file for the
How can I abort running a script if I determine it's taking too long?
Currently, I simply close the R window and re-open it. Thank you!
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I'm trying to estimate a two-tier model with varying intercepts and slopes
across 20 groups, with each group having about 50 observations and with no
group predictor. I use the command lmer(y~x+(1+x | group)). But the result
is a constant intercept (zero standard deviation, all 20 intercept values
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