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16 changes: 7 additions & 9 deletions README.Rmd
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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.

### 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.


## Installation

You can install the development version of SANple from [GitHub](https://github.com/) with:
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plot(out, estimated_clusters = clusters)
```

...
# 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*, 1–23.

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}
31 changes: 14 additions & 17 deletions README.md
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Expand Up @@ -16,21 +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.

### 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>.

## Installation

You can install the development version of SANple from
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#> Model estimated on 290 total observations and 2 groups
#> Total MCMC iterations: 3000
#> maxL: 50 - maxK: 50
#> Elapsed time: 1.583 secs
#> Elapsed time: 1.585 secs
clusters <- estimate_clusters(out, burnin = 2000)
clusters
#>
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<img src="man/figures/README-example-2.png" width="100%" />

# 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*, 1–23.

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.

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