updated Readme - conformed DOIs

README.Rmd

@@ -21,12 +21,6 @@ knitr::opts_chunk$set(
 
 The goal of SANple is to estimate Bayesian nested mixture models via MCMC methods. Specifically, the package implements the common atoms model (Denti et al., 2023), its finite version (D'Angelo et al., 2023), and a hybrid finite-infinite model (D'Angelo and Denti, 2023+). All models use Gaussian mixtures with a normal-inverse-gamma prior distribution on the parameters. Additional functions are provided to help analyzing the results of the fitting procedure.
 
-D’Angelo, L., Canale, A., Yu, Z., Guindani, M. (2023). Bayesian nonparametric analysis for the detection of spikes in noisy calcium imaging data. *Biometrics* 79(2), 1370--1382. doi:10.1111/biom.13626.
-
-D’Angelo, L., and Denti, F. (2023+). A finite-infinite shared atoms nested model for the Bayesian analysis of large grouped data sets. *Working paper* 0--23.
-
-Denti, F., Camerlenghi, F., Guindani, M., Mira, A., 2023. A Common Atoms Model for the Bayesian Nonparametric Analysis of Nested Data. *Journal of the American Statistical Association*. 118(541), 405--416. doi:10.1080/01621459.2021.1933499.
-
 ## Installation
 
 You can install the development version of SANple from [GitHub](https://github.com/) with:
@@ -53,4 +47,12 @@ out <- sample_fiSAN(nrep = 3000, y = y, group = g, beta = 1)
 out 
 ```
 
-...
+...
+
+# References
+
+D’Angelo, L., Canale, A., Yu, Z., Guindani, M. (2023). Bayesian nonparametric analysis for the detection of spikes in noisy calcium imaging data. *Biometrics* 79(2), 1370--1382. \doi{10.1111/biom.13626}.
+
+D’Angelo, L., and Denti, F. (2023+). A finite-infinite shared atoms nested model for the Bayesian analysis of large grouped data sets. *Working paper* 0--23.
+
+Denti, F., Camerlenghi, F., Guindani, M., Mira, A., 2023. A Common Atoms Model for the Bayesian Nonparametric Analysis of Nested Data. *Journal of the American Statistical Association*. 118(541), 405--416. \doi{10.1080/01621459.2021.1933499}.

README.md

@@ -16,19 +16,6 @@ models use Gaussian mixtures with a normal-inverse-gamma prior
 distribution on the parameters. Additional functions are provided to
 help analyzing the results of the fitting procedure.
 
-D’Angelo, L., Canale, A., Yu, Z., Guindani, M. (2023). Bayesian
-nonparametric analysis for the detection of spikes in noisy calcium
-imaging data. *Biometrics* 79(2), 1370–1382. <doi:10.1111/biom.13626>.
-
-D’Angelo, L., and Denti, F. (2023+). A finite-infinite shared atoms
-nested model for the Bayesian analysis of large grouped data sets.
-*Working paper* 0–23.
-
-Denti, F., Camerlenghi, F., Guindani, M., Mira, A., 2023. A Common Atoms
-Model for the Bayesian Nonparametric Analysis of Nested Data. *Journal
-of the American Statistical Association*. 118(541), 405–416.
-<doi:10.1080/01621459.2021.1933499>.
-
 ## Installation
 
 You can install the development version of SANple from
@@ -67,7 +54,21 @@ out
 #> Model estimated on 240 total observations and 2 groups 
 #> Total MCMC iterations: 3000 
 #> maxL: 50 - maxK: 50 
-#> Elapsed time: 1.142 secs
+#> Elapsed time: 1.435 secs
 ```
 
 …
+
+# References
+
+D’Angelo, L., Canale, A., Yu, Z., Guindani, M. (2023). Bayesian
+nonparametric analysis for the detection of spikes in noisy calcium
+imaging data. *Biometrics* 79(2), 1370–1382. .
+
+D’Angelo, L., and Denti, F. (2023+). A finite-infinite shared atoms
+nested model for the Bayesian analysis of large grouped data sets.
+*Working paper* 0–23.
+
+Denti, F., Camerlenghi, F., Guindani, M., Mira, A., 2023. A Common Atoms
+Model for the Bayesian Nonparametric Analysis of Nested Data. *Journal
+of the American Statistical Association*. 118(541), 405–416. .