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] 0.776 0.2101  0.00271        0.00645
beta[2] 1.258 0.2756  0.00356        0.00929
beta[3] 0.676 0.2789  0.00360        0.00776
beta[4] 1.342 0.2958  0.00382        0.00814
beta[5] 0.843 0.1862  0.00240        0.00708
beta[6] 1.215 0.2086  0.00269        0.00596
pi[1]   0.286 0.0891  0.00115        0.00161
pi[2]   0.423 0.0834  0.00108        0.00166
pi[3]   0.568 0.1139  0.00147        0.00244

2. Quantiles for each variable:

         2.5%   25%   50%   75% 97.5%
beta[1] 0.290 0.637 0.834 0.961 1.000
beta[2] 1.006 1.071 1.173 1.348 2.005
beta[3] 0.108 0.457 0.735 0.938 1.000
beta[4] 1.014 1.123 1.265 1.488 2.117
beta[5] 0.356 0.755 0.920 0.988 1.000
beta[6] 1.006 1.063 1.153 1.300 1.778
pi[1]   0.130 0.222 0.280 0.341 0.483
pi[2]   0.266 0.364 0.423 0.476 0.588
pi[3]   0.342 0.492 0.570 0.648 0.784

> 
> 
> 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