Error(s) in re-building vignettes:
  ...
--- re-building ‘aov.Rmd’ using rmarkdown
--- finished re-building ‘aov.Rmd’

--- re-building ‘betareg.Rmd’ using rmarkdown
--- finished re-building ‘betareg.Rmd’

--- re-building ‘binomial.Rmd’ using rmarkdown
--- finished re-building ‘binomial.Rmd’

--- re-building ‘continuous.Rmd’ using rmarkdown
--- finished re-building ‘continuous.Rmd’

--- re-building ‘count.Rmd’ using rmarkdown
--- finished re-building ‘count.Rmd’

--- re-building ‘glmer.Rmd’ using rmarkdown
--- finished re-building ‘glmer.Rmd’

--- re-building ‘jm.Rmd’ using rmarkdown
--- finished re-building ‘jm.Rmd’

--- re-building ‘lm.Rmd’ using rmarkdown
--- finished re-building ‘lm.Rmd’

--- re-building ‘mrp.Rmd’ using rmarkdown
pandoc-citeproc: Error in $: Incompatible API versions: encoded with [1,20] but attempted to decode with [1,17,5,4].
CallStack (from HasCallStack):
  error, called at ./Text/Pandoc/JSON.hs:111:48 in pandoc-types-1.17.5.4-5tHZ3B61A58JaKOMxwGQR4:Text.Pandoc.JSON
Error running filter /usr/bin/pandoc-citeproc:
Filter returned error status 1
Error: processing vignette 'mrp.Rmd' failed with diagnostics:
pandoc document conversion failed with error 83
--- failed re-building ‘mrp.Rmd’

--- re-building ‘polr.Rmd’ using rmarkdown
--- finished re-building ‘polr.Rmd’

--- re-building ‘pooling.Rmd’ using rmarkdown
--- finished re-building ‘pooling.Rmd’

--- re-building ‘priors.Rmd’ using rmarkdown
Loading required package: Rcpp
rstanarm (Version 2.19.3, packaged: 2020-02-11 05:16:41 UTC)
- Do not expect the default priors to remain the same in future rstanarm versions.
Thus, R scripts should specify priors explicitly, even if they are just the defaults.
- For execution on a local, multicore CPU with excess RAM we recommend calling
options(mc.cores = parallel::detectCores())
- bayesplot theme set to bayesplot::theme_default()
   * Does _not_ affect other ggplot2 plots
   * See ?bayesplot_theme_set for details on theme setting
Warning: There were 1 chains where the estimated Bayesian Fraction of Missing Information was low. See
http://mc-stan.org/misc/warnings.html#bfmi-low
Warning: Examine the pairs() plot to diagnose sampling problems

Warning: The largest R-hat is 1.9, indicating chains have not mixed.
Running the chains for more iterations may help. See
http://mc-stan.org/misc/warnings.html#r-hat
Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.
Running the chains for more iterations may help. See
http://mc-stan.org/misc/warnings.html#bulk-ess
Warning: Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.
Running the chains for more iterations may help. See
http://mc-stan.org/misc/warnings.html#tail-ess
Warning: Markov chains did not converge! Do not analyze results!
--- finished re-building ‘priors.Rmd’

--- re-building ‘rstanarm.Rmd’ using rmarkdown
Loading required package: Rcpp
rstanarm (Version 2.19.3, packaged: 2020-02-11 05:16:41 UTC)
- Do not expect the default priors to remain the same in future rstanarm versions.
Thus, R scripts should specify priors explicitly, even if they are just the defaults.
- For execution on a local, multicore CPU with excess RAM we recommend calling
options(mc.cores = parallel::detectCores())
- bayesplot theme set to bayesplot::theme_default()
   * Does _not_ affect other ggplot2 plots
   * See ?bayesplot_theme_set for details on theme setting
Warning: Found 1 observation(s) with a pareto_k > 0.7. We recommend calling 'loo' again with argument 'k_threshold = 0.7' in order to calculate the ELPD without the assumption that these observations are negligible. This will refit the model 1 times to compute the ELPDs for the problematic observations directly.

Warning: Found 1 observation(s) with a pareto_k > 0.7. We recommend calling 'loo' again with argument 'k_threshold = 0.7' in order to calculate the ELPD without the assumption that these observations are negligible. This will refit the model 1 times to compute the ELPDs for the problematic observations directly.

Warning in plot.psis_loo(loo_bglm_1, label_points = TRUE) :
  2.4% of Pareto k estimates are Inf/NA/NaN and not plotted.
Warning in plot.psis_loo(loo_bglm_2, label_points = TRUE) :
  2.4% of Pareto k estimates are Inf/NA/NaN and not plotted.
--- finished re-building ‘rstanarm.Rmd’

SUMMARY: processing the following file failed:
  ‘mrp.Rmd’

Error: Vignette re-building failed.
Execution halted