Nothing
`nsim` must be set to sample <greta array>s not in MCMC samples
the greta arrays `y` have distributions and are not in the MCMC samples, so cannot be calculated from the samples alone.
Set `nsim` if you want to sample them conditionally on the MCMC samples
`nsim` was greater than the number of posterior samples in values, so posterior samples had to be drawn with replacement
the target <greta array>s do not appear to be connected to those in the <greta_mcmc_list> object
`nsim` must be set to sample <greta array>s not in MCMC samples
the target <greta array>s are related to new variables that are not in the MCMC samples, so cannot be calculated from the samples alone.
Set `nsim` if you want to sample them conditionally on the MCMC samples
`calculate()` arguments must be <greta_array>s
The following object passed to `calculate()` is not a <greta array>:
"x"
Perhaps you forgot to explicitly name other arguments?
`calculate()` arguments must be <greta_array>s
The following object passed to `calculate()` is not a <greta array>:
"list(x = c(2, 1))"
Perhaps you forgot to explicitly name other arguments?
Please provide values for the following 1 <greta_array>:
`a`
a provided value has different number of elements than the <greta_array>
`trace_batch_size` must be a single numeric value greater than or equal to 1
`trace_batch_size` must be a single numeric value greater than or equal to 1
`trace_batch_size` must be a single numeric value greater than or equal to 1
the target <greta_array>s are related to variables that do not have distributions so cannot be sampled
sampling is not yet implemented for "hypergeometric" distributions
nsim must be a positive integer
However the value provided was: 0
nsim must be a positive integer
However the value provided was: -1
nsim must be a positive integer
However the value provided was: NA
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