zip and zinb don't work with MCMC and calculate?

[njtierney]

library(greta.distributions)
#> Loading required package: 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,
#>     tapply
dist_norm <- normal(0,1)
#> ℹ Initialising python and checking dependencies, this may take a moment.
#> ✔ Initialising python and checking dependencies ... done!
#> 
calculate(dist_norm, nsim = 10)
#> $dist_norm
#> , , 1
#> 
#>             [,1]
#>  [1,]  1.2500928
#>  [2,] -0.4346139
#>  [3,] -0.2413200
#>  [4,] -0.4308299
#>  [5,]  0.4692297
#>  [6,]  0.5229450
#>  [7,] -0.1046054
#>  [8,]  2.4158701
#>  [9,] -0.7425140
#> [10,]  0.3510102
m_norm <- model(dist_norm)
draws <- mcmc(m_norm, n_samples = 10, warmup = 10)
#> running 4 chains simultaneously on up to 8 CPU cores
#> 
#>     warmup                                             0/10 | eta:  ?s              warmup ========================================== 10/10 | eta:  0s          
#>   sampling                                             0/10 | eta:  ?s            sampling ========================================== 10/10 | eta:  0s

zip <- zero_inflated_poisson(lambda = 2, pi = 0.2)
# fails
calculate(zip, nsim = 10)
#> cannot compute Sub as input #1(zero-based) was expected to be a double tensor
#> but is a float tensor [Op:Sub] name:
# fails
m <- model(zip)
#> Error in `check_unfixed_discrete_distributions()` at greta/R/greta_model_class.R:97:3:
#> ! Model contains a discrete random variable that doesn't have a fixed
#>   value, so inference cannot be carried out.

# zinb

zinb <- zero_inflated_negative_binomial(size = 2, prob= 0.2, pi = 0.10)
calculate(zinb, nsim = 10)
#> $zinb
#> , , 1
#> 
#>       [,1]
#>  [1,]   10
#>  [2,]   18
#>  [3,]   24
#>  [4,]    1
#>  [5,]    1
#>  [6,]   15
#>  [7,]    6
#>  [8,]    5
#>  [9,]   12
#> [10,]    3
m <- model(zinb)
#> Error in `check_unfixed_discrete_distributions()` at greta/R/greta_model_class.R:97:3:
#> ! Model contains a discrete random variable that doesn't have a fixed
#>   value, so inference cannot be carried out.
mcmc(m)
#> Error: object 'm' not found

^{Created on 2024-12-18 with reprex v2.1.1}

Session info

sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
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#>  language (EN)
#>  collate  en_US.UTF-8
#>  ctype    en_US.UTF-8
#>  tz       Australia/Brisbane
#>  date     2024-12-18
#>  pandoc   3.2.1 @ /opt/homebrew/bin/ (via rmarkdown)
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#> 
#> ─ Python configuration ───────────────────────────────────────────────────────
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#> ──────────────────────────────────────────────────────────────────────────────

Note that we should also check that MCMC and calculate work with new distributions, and this should also be added to templates for tests