diff --git a/.gitignore b/.gitignore
index 368dbcfe..f9df55b6 100644
--- a/.gitignore
+++ b/.gitignore
@@ -3,4 +3,4 @@ gemtc.Rcheck
 *.swp
 gemtc_*.tar.gz
 *.so
-*.o
+*.o
\ No newline at end of file
diff --git a/gemtc/DESCRIPTION b/gemtc/DESCRIPTION
index a58d8b89..65c4d3fb 100644
--- a/gemtc/DESCRIPTION
+++ b/gemtc/DESCRIPTION
@@ -1,5 +1,5 @@
 Package: gemtc
-Version: 1.0-2
+Version: 1.0-2.9000
 Date: 2023-06-21
 Title: Network Meta-Analysis Using Bayesian Methods
 Author: Gert van Valkenhoef, Joel Kuiper
diff --git a/gemtc/NEWS.md b/gemtc/NEWS.md
index 9eb9f9c1..71c42115 100644
--- a/gemtc/NEWS.md
+++ b/gemtc/NEWS.md
@@ -1,3 +1,10 @@
+gemtc 1.0-2.9000
+===========
+
+Released 2024-XX-XX
+
+* Add addtional n.burnin argument to the mtc.run and mtc.sample. The update is connected with the fact that the nadapt is not equal to nburnin.
+
 gemtc 1.0-2
 ===========
 
diff --git a/gemtc/R/mtc.run.R b/gemtc/R/mtc.run.R
index b88564bd..fbed115e 100644
--- a/gemtc/R/mtc.run.R
+++ b/gemtc/R/mtc.run.R
@@ -19,7 +19,8 @@ mtc.model.run <- function(network, type, ...) {
 
 # If is.na(sampler), a sampler will be chosen based on availability, in this order:
 # JAGS, BUGS. When the sampler is BUGS, BRugs or R2WinBUGS will be used.
-mtc.run <- function(model, sampler=NA, n.adapt=5000, n.iter=20000, thin=1) {
+mtc.run <- function(model, sampler=NA, n.adapt=5000, n.iter=20000, thin=1, n.burnin=0) {
+  
   if (!is.na(sampler)) {
     if (sampler %in% c("JAGS", "rjags")) {
       warning("Setting the sampler is deprecated.")
@@ -28,7 +29,7 @@ mtc.run <- function(model, sampler=NA, n.adapt=5000, n.iter=20000, thin=1) {
     }
   }
 
-  result <- mtc.sample(model, n.adapt=n.adapt, n.iter=n.iter, thin=thin)
+  result <- mtc.sample(model, n.adapt=n.adapt, n.iter=n.iter, thin=thin, n.burnin=n.burnin)
 
   result <- c(result, list(model = model))
   class(result) <- "mtc.result"
@@ -44,7 +45,7 @@ mtc.build.syntaxModel <- function(model) {
   )
 }
 
-mtc.sample <- function(model, n.adapt=n.adapt, n.iter=n.iter, thin=thin) {
+mtc.sample <- function(model, n.adapt, n.iter, thin, n.burnin) {
   # generate JAGS model
   syntax <- mtc.build.syntaxModel(model)
 
@@ -64,6 +65,9 @@ mtc.sample <- function(model, n.adapt=n.adapt, n.iter=n.iter, thin=thin) {
     inits=syntax[['inits']],
     n.chains=model[['n.chain']],
     n.adapt=n.adapt)
+  
+  if (n.burnin > 0) update(jags, n.iter=n.burnin)
+  
   samples <- rjags::coda.samples(jags, variable.names=vars,
                                  n.iter=n.iter, thin=thin)
   unlink(file.model)
diff --git a/gemtc/man/mtc.run.Rd b/gemtc/man/mtc.run.Rd
index bf767a1e..26caf0d1 100644
--- a/gemtc/man/mtc.run.Rd
+++ b/gemtc/man/mtc.run.Rd
@@ -14,7 +14,7 @@ The function \code{mtc.run} is used to generate samples from a object of type \c
 The resulting \code{mtc.result} object can be coerced to an \code{mcmc.list} for further analysis of the dataset using the \code{coda} package.
 }
 \usage{
-mtc.run(model, sampler = NA, n.adapt = 5000, n.iter = 20000, thin = 1)
+mtc.run(model, sampler = NA, n.adapt = 5000, n.iter = 20000, thin = 1, n.burnin = 0)
 
 \method{summary}{mtc.result}(object, ...)
 \method{plot}{mtc.result}(x, ...)
@@ -28,6 +28,7 @@ mtc.run(model, sampler = NA, n.adapt = 5000, n.iter = 20000, thin = 1)
   \item{n.adapt}{Amount of adaptation (or tuning) iterations.}
   \item{n.iter}{Amount of simulation iterations.}
   \item{thin}{Thinning factor.}
+  \item{n.burnin}{Amount of burn-in iterations. Has to be positive number.}
 
   \item{object}{Object of S3 class \code{mtc.result}.}
   \item{x}{Object of S3 class \code{mtc.result}.}