Running examples in ‘snSMART-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: group_seq
> ### Title: BJSM method for interim analysis and final analysis of group
> ###   sequential trial design
> ### Aliases: group_seq print.summary.group_seq print.group_seq
> 
> ### ** Examples
> 
> mydata <- groupseqDATA_look1
> 
> result1 <- group_seq(
+   data = mydata, interim = TRUE, drop_threshold_pair = c(0.5, 0.4),
+   prior_dist = c("beta", "beta", "pareto"), pi_prior = c(0.4, 1.6, 0.4, 1.6, 0.4, 1.6),
+   beta_prior = c(1.6, 0.4, 3, 1), MCMC_SAMPLE = 6000, n.adapt = 1000, n_MCMC_chain = 1
+ )

Interim Analysis Outcome:

Threshold tau_l is set to: 
0.5

Threshold psi_l is set to: 
0.4

Step 1: Arm C's interim posterior probability of having the greatest response is bigger than threshold 
0.5


Step 2: Arm A's interim posterior probability of having the lowest response is higher

Arm A is dropped



> 
> summary(result1)
Arm A is dropped

Iterations = 1101:7100
Thinning interval = 1 
Number of chains = 1 
Sample size per chain = 6000 

1. Empirical mean and standard deviation for each variable,
   plus standard error of the mean:

         Mean     SD Naive SE Time-series SE
beta[1] 0.777 0.2150  0.00278        0.00644
beta[2] 1.246 0.2883  0.00372        0.01093
beta[3] 0.695 0.2787  0.00360        0.00781
beta[4] 1.350 0.3187  0.00411        0.00897
beta[5] 0.838 0.1957  0.00253        0.00697
beta[6] 1.208 0.2051  0.00265        0.00651
pi[1]   0.290 0.0899  0.00116        0.00182
pi[2]   0.423 0.0838  0.00108        0.00178
pi[3]   0.572 0.1093  0.00141        0.00256

2. Quantiles for each variable:

         2.5%   25%   50%   75% 97.5%
beta[1] 0.281 0.634 0.839 0.966 1.000
beta[2] 1.005 1.064 1.153 1.320 2.051
beta[3] 0.101 0.479 0.770 0.953 1.000
beta[4] 1.011 1.115 1.262 1.504 2.182
beta[5] 0.307 0.753 0.920 0.987 1.000
beta[6] 1.005 1.063 1.151 1.287 1.736
pi[1]   0.135 0.226 0.284 0.347 0.479
pi[2]   0.263 0.366 0.422 0.479 0.590
pi[3]   0.353 0.497 0.574 0.648 0.779

> 
> 
> mydata <- groupseqDATA_full
> result2 <- group_seq(
+   data = mydata, interim = FALSE, prior_dist = c("beta", "beta", "pareto"),
+   pi_prior = c(0.4, 1.6, 0.4, 1.6, 0.4, 1.6),
+   beta_prior = c(1.6, 0.4, 3, 1), MCMC_SAMPLE = 6000, n.adapt = 1000,
+   n_MCMC_chain = 1, ci = 0.95, DTR = TRUE
+ )

Error in update.jags(model, n.iter, ...) : Error in node beta[5]
Slicer stuck at value with infinite density

Calls: group_seq ... do.call -> <Anonymous> -> jags.samples -> update.jags
Execution halted