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If mixture is used to define distribution, and I try to run calculate on a parameter of the model with both posterior samples provided through values arg and number of simulations through nsim arg, then I get hit with error argument is of length zero.
It seems to have something to do with how the mixture distribution node is defined in dag, maybe some attribute is missing.
Note this error does not occur if running calculate without specifying either values or nsim
library(greta)
#> #> Attaching package: 'greta'#> The following objects are masked from 'package:stats':#> #> binomial, cov2cor, poisson#> The following objects are masked from 'package:base':#> #> %*%, apply, backsolve, beta, chol2inv, colMeans, colSums, diag,#> eigen, forwardsolve, gamma, identity, rowMeans, rowSums, sweep,#> tapplyweights_raw<- uniform(0, 1, dim=1)
#> ℹ Initialising python and checking dependencies, this may take a moment.#> ✔ Initialising python and checking dependencies ... done!#> weights<- c(weights_raw, 1-weights_raw)
alpha<-beta<- normal(0,1)
a<- mixture(normal(alpha, 0.5),
normal(beta, 0.5),
weights=weights
)
m<- model(a)
fit<- mcmc(m, n_samples=500)
#> running 4 chains simultaneously on up to 8 CPU cores#> #> warmup 0/1000 | eta: ?s warmup == 50/1000 | eta: 24s warmup ==== 100/1000 | eta: 13s warmup ====== 150/1000 | eta: 9s
calculate(weights, values=fit, nsim=10)
#> argument is of length zero
If
mixture
is used to define distribution, and I try to runcalculate
on a parameter of the model with both posterior samples provided throughvalues
arg and number of simulations throughnsim
arg, then I get hit with errorargument is of length zero
.It seems to have something to do with how the mixture distribution node is defined in dag, maybe some attribute is missing.
Note this error does not occur if running
calculate
without specifying eithervalues
ornsim
Created on 2024-10-15 with reprex v2.1.1
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