Package check result: ERROR

Check: examples, Result: ERROR
  Running examples in ‘pencal-Ex.R’ failed
  The error most likely occurred in:
  
  > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
  > ### Name: fit_mlpmms
  > ### Title: Step 1 of PRC-MLPMM (estimation of the linear mixed models)
  > ### Aliases: fit_mlpmms
  > 
  > ### ** Examples
  > 
  > ## No test: 
  > # generate example data
  > set.seed(123)
  > n.items = c(4,2,2,3,4,2)
  > simdata = simulate_prcmlpmm_data(n = 100, p = length(n.items),  
  +              p.relev = 3, n.items = n.items, 
  +              type = 'u+b', seed = 1)
  >  
  > # specify options for cluster bootstrap optimism correction
  > # procedure and for parallel computing 
  > do.bootstrap = FALSE
  > # IMPORTANT: set do.bootstrap = TRUE to compute the optimism correction!
  > n.boots = ifelse(do.bootstrap, 100, 0)
  > more.cores = FALSE
  > # IMPORTANT: set more.cores = TRUE to speed computations up!
  > if (!more.cores) n.cores = 2
  > if (more.cores) {
  +    # identify number of available cores on your machine
  +    n.cores = parallel::detectCores()
  +    if (is.na(n.cores)) n.cores = 2
  + }
  > 
  > # step 1 of PRC-MLPMM: estimate the MLPMMs
  > y.names = vector('list', length(n.items))
  > for (i in 1:length(n.items)) {
  +   y.names[[i]] = paste('marker', i, '_', 1:n.items[i], sep = '')
  + }
  > 
  > step1 = fit_mlpmms(y.names, fixefs = ~ contrast(age),  
  +                  ranef.time = age, randint.items = TRUE, 
  +                  long.data = simdata$long.data, 
  +                  surv.data = simdata$surv.data,
  +                  t.from.base = t.from.base,
  +                  n.boots = n.boots, n.cores = n.cores)
  Sorting long.data by subject id
  Sorting surv.data by subject id
  Preliminary step: remove measurements taken after event / censoring.
  Removed: 0 measurements. Retained: 400 measurements.
  This computation will be run in parallel 
  Estimating the MLPMMs on the original dataset...
  Error in { : 
    task 1 failed - "Estimation of the MLPMM for the 1-th latent biological process (on the original dataset) failed. Try to increase maxiter, or (if this fails) to change the 1-th element of randint.items. See also point C of the Details section of ?multlcmm"
  Calls: fit_mlpmms -> %dopar% -> <Anonymous>
  Execution halted