Minor reformatting of DESCRIPTION, updated date

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: EMJMCMC
 Type: Package
-Title: Evolutionary Mode Jumping Markov Chain Monte Carlo Expert Toolbox 
+Title: Evolutionary Mode Jumping Markov Chain Monte Carlo Expert Toolbox
 Version: 1.5.0
-Date: 2024-04-23
+Date: 2024-04-25
 Authors@R:
   c(
     person("Aliaksandr", "Hubin", email = "aliaksah@math.uio.no", role = c("aut")),
@@ -11,14 +11,11 @@ Authors@R:
     person("Florian", "Frommlet", role = c("ctb"))
   )
 Maintainer: Waldir Leoncio <w.l.netto@medisin.uio.no>
-Description: Implementation of the Mode Jumping Markov Chain Monte Carlo algorithm from Hubin, A., Storvik, G. (2018) <doi:10.1016/j.csda.2018.05.020>, Genetically Modified Mode Jumping Markov Chain Monte Carlo from Hubin, A., Storvik, G., & Frommlet, F. (2020) <doi:10.1214/18-BA1141>, Hubin, A., Storvik, G., & Frommlet, F. (2021) <doi:10.1613/jair.1.13047>, and Hubin, A., Heinze, G., & De Bin, R. (2023) <doi:10.3390/fractalfract7090641>, and Reversible Genetically Modified Mode Jumping Markov Chain Monte Carlo from Hubin, A., Frommlet, F., & Storvik, G. (2021) <doi:10.48550/arXiv.2110.05316>.
-  which allow for estimating posterior model
-  probabilities and Bayesian model averaging across a wide set of Bayesian models including linear, generalized linear, generalized linear mixed, generalized nonlinear, generalized nonlinear mixed, and logic regression models.
+Description: Implementation of the Mode Jumping Markov Chain Monte Carlo algorithm from Hubin, A., Storvik, G. (2018) <doi:10.1016/j.csda.2018.05.020>, Genetically Modified Mode Jumping Markov Chain Monte Carlo from Hubin, A., Storvik, G., & Frommlet, F. (2020) <doi:10.1214/18-BA1141>, Hubin, A., Storvik, G., & Frommlet, F. (2021) <doi:10.1613/jair.1.13047>, and Hubin, A., Heinze, G., & De Bin, R. (2023) <doi:10.3390/fractalfract7090641>, and Reversible Genetically Modified Mode Jumping Markov Chain Monte Carlo from Hubin, A., Frommlet, F., & Storvik, G. (2021) <doi:10.48550/arXiv.2110.05316>, which allow for estimating posterior model probabilities and Bayesian model averaging across a wide set of Bayesian models including linear, generalized linear, generalized linear mixed, generalized nonlinear, generalized nonlinear mixed, and logic regression models.
 License: GPL
 Depends: R (>= 3.4.1), bigmemory
 Imports: glmnet, biglm, hash, BAS, stringi, parallel, methods, speedglm, stats
 RoxygenNote: 7.3.1
-Suggests:
-    testthat (>= 3.0.0), bindata, clusterGeneration, reshape2
+Suggests: testthat (>= 3.0.0), bindata, clusterGeneration, reshape2
 Config/testthat/edition: 3
 Encoding: UTF-8