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] 0.768 0.2148  0.00277        0.00606
beta[2] 1.239 0.2733  0.00353        0.01000
beta[3] 0.695 0.2774  0.00358        0.00874
beta[4] 1.346 0.3073  0.00397        0.00850
beta[5] 0.847 0.1867  0.00241        0.00788
beta[6] 1.202 0.1912  0.00247        0.00527
pi[1]   0.287 0.0897  0.00116        0.00164
pi[2]   0.424 0.0840  0.00108        0.00178
pi[3]   0.574 0.1114  0.00144        0.00227

2. Quantiles for each variable:

         2.5%   25%   50%   75% 97.5%
beta[1] 0.274 0.621 0.828 0.957 1.000
beta[2] 1.005 1.060 1.153 1.323 1.955
beta[3] 0.112 0.481 0.762 0.953 1.000
beta[4] 1.011 1.115 1.266 1.489 2.142
beta[5] 0.326 0.773 0.924 0.987 1.000
beta[6] 1.005 1.063 1.149 1.283 1.701
pi[1]   0.130 0.222 0.279 0.346 0.479
pi[2]   0.268 0.364 0.422 0.480 0.593
pi[3]   0.351 0.498 0.577 0.652 0.785

> 
> 
> 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[1]
Slicer stuck at value with infinite density

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