From 76770a3bf46b526fbc890ea42b5370180f9c8fec Mon Sep 17 00:00:00 2001 From: fradenti Date: Tue, 3 Oct 2023 16:56:35 +0200 Subject: [PATCH] updated Readme - conformed DOIs --- README.Rmd | 16 +++++++++------- README.md | 29 +++++++++++++++-------------- 2 files changed, 24 insertions(+), 21 deletions(-) diff --git a/README.Rmd b/README.Rmd index e9df18c..3b3c587 100644 --- a/README.Rmd +++ b/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 ``` -... \ No newline at end of file +... + +# 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}. diff --git a/README.md b/README.md index dd7c0bb..4d4c0bb 100644 --- a/README.md +++ b/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. . - -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. -. - ## 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. .