Hi, I am writing an MCMC likelihood function that comes from a dynamic
model. I have about 50 state variables for several thousand individuals
that each get updated iteratively over time. However, some individuals'
variables get updated at some type steps but not at others (because they
are inactive). I'd like to be able to write something of the sort
k = 50
n = 1000
states = rand(n, k)
typeof!(states, "DataFrame")
function dynupdate(states, active)
with(states[active,:], {
x1 = x1 .* 2
x2 = par1 .* x3 .*x 2
x3 = par3 .* (x1 + x3)^2})
return(states)
}
Forgive the sloppy coding, I'm quite new to Julia. I'm not sure the best
way to do this. The other complication is that I want x1,x2,x3 to all
depend on their value at the last time period. If I update x1 first, then
x2 will depend on the updated version of x1 and not the past one. I could
obviously create x1new, x2new, x3new and then update them in states at the
end, but I'm wondering whats the fastest, most elegant way to do this.
Also, I am struggling to understand how to navigate function documentation
in Julia. When I type help(with) it gives me almost no information on that
function. with() is not an easy thing to search for on google either so I
have no idea what with() does. What's the best way to learn more about
functions in julia? In R, I rely on the help() and example() a lot.
Thanks!
Steve
