## Work in progress

Zheng, X., Kottas, A. and Sanso, B.
Mixture modeling for temporal point processes with memory.

Kang, J. and Kottas, A.
Structured mixture of continuation-ratio logits models for ordinal regression.

Kang, J. and Kottas, A.
Flexible Bayesian modeling for longitudinal binary and ordinal responses.

Zhao, C. and Kottas, A.
Modelling for Poisson process intensities over irregular spatial domains.

Yan, Y. and Kottas, A.
A new family of error distributions for Bayesian quantile regression.

Poynor, V. and Kottas, A.
Bayesian nonparametric modeling for mean residual life regression.

## Publications

### Book chapters

DeYoreo, M. and Kottas, A. (2020).
``Bayesian nonparametric density regression for ordinal responses''

In *Flexible Bayesian Regression Modelling*, J.-L. Dortet-Bernadet,
Y. Fan, D. Nott and M.S. Smith (Editors), Elsevier, pp. 65-89.

Kottas, A. (2016).
``Bayesian nonparametric modeling for disease incidence data''

In *Handbook of Spatial Epidemiology*,
A.B. Lawson, S. Banerjee, R.P. Haining and M.D. Ugarte (Editors),
Chapman and Hall/CRC, pp. 363-374.

(An earlier version is available as
SOE Technical Report 2015-13.)

Kottas, A. and Fronczyk, K. (2013).
``Flexible Bayesian modelling for clustered categorical responses in
developmental toxicology''

In *Bayesian Theory and Applications*, P. Damien,
P. Dellaportas, N.G. Polson and D.A. Stephens (Editors), Oxford
University Press, pp. 70-83.

(An earlier version is available as
SOE Technical Report 2012-02.)

### Journal papers

**59.**
Li, Y., Lee, J. and Kottas, A.
``Bayesian nonparametric Erlang mixture modeling for survival analysis."

To appear in *Computational Statistics and Data Analysis*.

(An earlier version is available as
SOE Technical Report 2022-11.)

**58.**
Zheng, X., Kottas, A. and Sanso, B. (2023).
Nearest-neighbor mixture models for non-Gaussian spatial
processes.

*Bayesian Analysis*, 18, 1191-1222.

**[GitHub
link for code]**

**57.**
Zheng, X., Kottas, A. and Sanso, B. (2023).
Bayesian geostatistical modeling for discrete-valued processes.

*Environmetrics*, 34(7), e2805.

**[GitHub
link for code]**

**56.**
Heiner, M. and Kottas, A. (2022).
Bayesian nonparametric density autoregression with lag selection.

*Bayesian Analysis*, 17, 1245-1273.

**[GitHub
link for code]**

**55.**
Heiner, M. and Kottas, A. (2022).
Estimation and selection for high-order Markov chains with Bayesian
mixture transition distribution models.

*Journal of Computational and Graphical Statistics*, 31, 100-112.

(An earlier version is available as
stat.ME arXiv: 1906.10781
paper.)

**[GitHub
link for code]**

**54.**
Zheng, X., Kottas, A. and Sanso, B. (2022).
On construction and estimation of stationary mixture transition distribution models.

*Journal of Computational and Graphical Statistics*, 31, 283-293.

(An earlier version is available as
stat.ME arXiv:2010.12696
paper.)

**[GitHub
link for code]**

**53.**
Heiner, M. and Kottas, A. (2022).
Autoregressive density modeling with the Gaussian process mixture transition distribution.

*Journal of Time Series Analysis*, 43, 157-177.

(An earlier version is available as
stat.ME arXiv:2007.09279 paper.)

**52.**
Kim, H. and Kottas, A. (2022).
Erlang mixture modeling for Poisson process intensities.

*Statistics and Computing*, 32:3.

**[GitHub
link for code]**

**51.**
Xiao, S., Kottas, A., Sanso, B. and Kim, H. (2021).
Nonparametric Bayesian modeling and estimation for renewal processes.

*Technometrics*, 63, 100-115.

(An earlier version is available as
SOE Technical Report 2018-05.)

**50.**
Richardson, R., Kottas, A. and Sanso, B. (2020).
Spatio-temporal modelling using integro-difference equations with
bivariate stable kernels.

*Journal of the Royal Statistical Society, Series B*, 82,
1371-1392.

(An earlier version is available as
SOE Technical Report 2017-02.)

**49.**
Heiner, M., Kottas, A. and Munch, S. (2019).
Structured priors for sparse probability vectors with application to
model selection in Markov chains.

*Statistics and Computing*, 29, 1077-1093.

(An earlier version is available as
SOE Technical Report 2018-06.)

**[GitHub
link for code]**

**48.**
Cadonna, A., Kottas, A. and Prado, R. (2019).
Bayesian spectral modeling for multiple time series.

*Journal of the American Statistical Association*, 114, 1838-1853.

(An earlier version is available as
SOE Technical Report 2016-15.)

**47.**
Poynor, V. and Kottas, A. (2019).
Nonparametric Bayesian inference for mean residual life functions in survival analysis.

*Biostatistics*, 20, 240-255.

(An earlier version is available as
stat.ME arXiv:1411.7481 paper.)

**46.**
DeYoreo, M. and Kottas, A. (2018).
Modeling for dynamic ordinal regression relationships: An application
to estimating maturity of rockfish in California.

*Journal of the American Statistical Association*, 113, 68-80.

(An earlier version is available as
SOE Technical Report 2015-15.)

**45.**
DeYoreo, M. and Kottas, A. (2018).
Bayesian nonparametric modeling for multivariate ordinal regression.

*Journal of Computational and Graphical Statistics*, 27, 71-84.

(An earlier version is available as
SOE Technical Report 2015-14.)

**44.**
Richardson, R., Kottas, A. and Sanso, B. (2018).
Bayesian nonparametric modeling for integro-difference equations.

*Statistics and Computing*, 28, 87-101.

(An earlier version is available as
SOE Technical Report 2016-06.)

**43.**
Fronczyk, K. and Kottas, A. (2017).
Risk assessment for toxicity experiments with discrete and continuous
outcomes: A Bayesian nonparametric approach.

*Journal of Agricultural, Biological, and Environmental Statistics*,
22, 585-601.

(An earlier version is available as
SOE Technical Report 2014-06.)

**42.**
DeYoreo, M. and Kottas, A. (2017).
A Bayesian nonparametric Markovian model for nonstationary time series.

*Statistics and Computing*, 27, 1525-1538.

(An earlier version is available as
SOE Technical Report 2016-05.)

**41.**
Rodriguez, A., Wang, Z. and Kottas, A. (2017).
Assessing systematic risk in the S&P500 index between 2000 and 2011:
A Bayesian nonparametric approach.

*The Annals of Applied Statistics*, 11, 527-552.

(An earlier version is available as
SOE Technical Report 2017-01.)

**40.**
Cadonna, A., Kottas, A. and Prado, R. (2017).
Bayesian mixture modeling for spectral density estimation.

*Statistics and Probability Letters*, 125, 189-195.

(An earlier version is available as
SOE Technical Report 2015-04.)

**39.**
Richardson, R., Kottas, A. and Sanso, B. (2017).
Flexible integro-difference equation modeling for spatio-temporal data.

*Computational Statistics and Data Analysis*, 109, 182-198.

(An earlier version is available as
SOE Technical Report 2014-10.)

**38.**
DeYoreo, M. and Kottas, A. (2015).
A fully nonparametric modeling approach to binary regression.

*Bayesian Analysis*, 10, 821-847.

**37.**
Xiao, S., Kottas, A. and Sanso, B. (2015).
Modeling for seasonal marked point processes: An analysis of evolving
hurricane occurrences.

*The Annals of Applied Statistics*, 9, 353-382.

(An earlier version is available as
SOE Technical Report 2013-16.)

**36.**
Fellingham, G.W., Kottas, A. and Hartman, B.M. (2015).
Bayesian nonparametric predictive modeling of group health claims.

*Insurance: Mathematics and Economics*, 60, 1-10.

(An earlier version is available as
SOE Technical Report 2014-13.)

**35.**
Fronczyk, K. and Kottas, A. (2014).
A Bayesian nonparametric modeling framework for developmental
toxicity studies (with discussion).

*Journal of the American Statistical Association*, 109,
873-893.

(An earlier version is available as
SOE Technical Report 2010-11.)

**34.**
Farah, M. and Kottas, A. (2014).
Bayesian inference for sensitivity analysis of computer simulators,
with an application to radiative transfer models.

*Technometrics*, 56, 159-173.

(An earlier version is available as
SOE Technical Report 2010-15.)

**33.**
Fronczyk, K. and Kottas, A. (2014).
A Bayesian approach to the analysis of quantal bioassay studies
using nonparametric mixture models.

*Biometrics*, 70, 95-102.

(An earlier version is available as
SOE Technical Report 2012-01.)

**32.**
Kiziltan, B., Kottas, A., DeYoreo, M. and Thorsett, S.E. (2013).
The neutron star mass distribution.

*The Astrophysical Journal*, 778:66 (12pp).

(An earlier version is available as
SOE Technical Report 2010-35.)

**31.**
Farah, M., Kottas, A. and Morris, R.D. (2013).
An application of semiparametric Bayesian isotonic regression to the
study of radiation effects in spaceborne microelectronics.

*Journal of the Royal Statistical Society, Series C*, 62, 3-24.

(An earlier version is available as
SOE Technical Report 2010-13.)

**30.**
Kottas, A., Wang, Z. and Rodriguez, A. (2012).
Spatial modeling for risk assessment of extreme values from
environmental time series: a Bayesian nonparametric approach.

*Environmetrics* (Special Issue on "Quantitative
Risk Assessment"), 23, 649-662.

(An earlier version is available as
SOE Technical Report 2012-17.)

**29.**
Taddy, M. and Kottas, A. (2012).
Mixture modeling for marked Poisson processes.

*Bayesian Analysis*, 7, 335-362.

**28.**
Fronczyk, K., Kottas, A. and Munch, S. (2012).
Flexible modeling for stock-recruitment relationships using
Bayesian nonparametric mixtures.

*Environmental and Ecological Statistics*, 19, 183-204.

(An earlier version is available as
SOE Technical Report 2009-17.)

**27.**
Kottas, A., Behseta, S., Moorman, D.E., Poynor, V. and Olson, C. (2012).
Bayesian nonparametric analysis of neuronal intensity rates.

*Journal of Neuroscience Methods*, 203, 241-253.

(An earlier version is available as
SOE Technical Report 2011-20.)

**26.**
Kottas, A. and Fellingham, G.W. (2012).
Bayesian semiparametric modeling and inference with mixtures of
symmetric distributions.

*Statistics and Computing*, 22, 93-106.

**25.**
Kottas, A. (2011).
Bayesian semiparametric modeling for stochastic precedence, with
applications in epidemiology and survival analysis.

*Lifetime Data Analysis* (Special Issue on
"Bayesian Models for Survival Data"), 17, 135-155.

(An earlier version is available as
SOE Technical Report 2009-27.)

**24.**
Taddy, M. and Kottas, A. (2010).
A Bayesian nonparametric approach to inference for quantile regression.

*Journal of Business and Economic Statistics*, 28, 357-369.

(An earlier version is available as
AMS Technical Report 2007-21.)

**23.**
Carlson, S.M., Kottas, A. and Mangel, M. (2010).
Bayesian analysis of size-dependent overwinter mortality from
size-frequency distributions.

*Ecology*, 91, 1016-1024.

**22.**
Kottas, A. and Behseta, S. (2010).
Bayesian nonparametric modeling for comparison of single-neuron
firing intensities.

*Biometrics*, 66, 277-286.

(An earlier version is available as
AMS Technical Report 2008-4.)

**21.**
Taddy, M. and Kottas, A. (2009).
Markov switching Dirichlet process mixture regression.

*Bayesian Analysis*, 4, 793-816.

**20.**
Bayarri, M.J., Berger, J.O., Kennedy, M.C., Kottas, A.,
Paulo, R., Sacks, J., and Cafeo, J.A., Lin, C.H., Tu, J. (2009).

Predicting vehicle crashworthiness: Validation of computer models for
functional and hierarchical data.

*Journal of the American Statistical Association*, 104, 929-943.

**19.**
Kottas, A. and Krnjajic, M. (2009).
Bayesian semiparametric modelling in quantile regression.

*Scandinavian Journal of Statistics*, 36, 297-319.

(An earlier version is available as
AMS Technical Report 2005-6.)

**18.**
Munch, S.B. and Kottas, A. (2009).
A Bayesian modeling approach for determining productivity regimes and
their characteristics.

*Ecological Applications*, 19, 527-537.

(An earlier version is available as
AMS Technical Report 2008-6.)

**17.**
Morris, R.D., Kottas, A., Taddy, M., Furfaro, R. and Ganapol,
B.D. (2008). A statistical framework for the sensitivity analysis of
radiative transfer models.

*IEEE Transactions on Geoscience and Remote Sensing*, 46,
4062-4074.

**16.**
Hanson, T., Kottas, A. and Branscum, A. (2008).
Modeling stochastic order in the analysis of ROC data: Bayesian
nonparametric approaches.

*Journal of the Royal Statistical Society, Series C*, 57, 207-225.

**15.**
Kottas, A., Duan, J. and Gelfand, A.E. (2008).
Modeling disease incidence data with spatial and spatio-temporal
Dirichlet process mixtures.

*Biometrical Journal*, 50, 29-42.

**14.**
Krnjajic, M., Kottas, A. and Draper, D. (2008).
Parametric and nonparametric Bayesian model specification:
A case study involving models for count data.

*Computational Statistics & Data Analysis*, 52, 2110-2128.

**13.**
Viswanath, K., Obraczka, K., Kottas, A. and Sanso, B. (2007).
Statistical equivalent models for computer
simulators with an application to the Random Waypoint Mobility Model.

*SIMULATION*, 83, 157-172.

**12.**
Kottas, A. and Sanso, B. (2007).
Bayesian mixture modeling for spatial Poisson process
intensities, with applications to extreme value analysis.

*Journal of Statistical Planning and Inference*
(Special Issue on "Bayesian Inference in Stochastic Processes"),
137, 3151-3163.

**11.**
Kottas, A. (2006). Nonparametric Bayesian survival analysis
using mixtures of Weibull distributions.

*Journal of Statistical Planning and Inference*, 136, 578-596.

**10.**
Kottas, A., Mueller, P. and Quintana, F. (2005).
Nonparametric Bayesian modeling for multivariate ordinal data.

*Journal of Computational and Graphical Statistics*, 14,
610-625.

**9.**
Gelfand, A.E., Kottas, A. and MacEachern, S.N. (2005).
Bayesian nonparametric spatial modeling with Dirichlet process
mixing.

*Journal of the American Statistical Association*,
100, 1021-1035.

**8.**
Munch, S.B., Kottas, A. and Mangel, M. (2005). Bayesian
nonparametric analysis of stock-recruitment relationships.

*Canadian Journal of Fisheries & Aquatic Sciences*,
62, 1808-1821.

**7.**
Gelfand, A.E. and Kottas, A. (2003). Bayesian semiparametric
regression for median residual life.

* Scandinavian Journal of Statistics*, 30, 651-665.

**6.**
Kottas, A., Branco, M.D. and Gelfand, A.E. (2002). A
nonparametric Bayesian modeling approach for cytogenetic
dosimetry.

* Biometrics*, 58, 593-600.

**5.**
Gelfand, A.E. and Kottas, A. (2002). A computational approach
for full nonparametric Bayesian inference under Dirichlet process
mixture models.

* Journal of Computational and Graphical Statistics*, 11, 289-305.

**4.**
Kottas, A. and Gelfand, A.E. (2001). Modeling variability order:
A semiparametric Bayesian approach.

*Methodology and
Computing in Applied Probability*, 3, 427-442.

**3.**
Kottas, A. and Gelfand, A.E. (2001). Bayesian semiparametric
median regression modeling.

*Journal of the
American Statistical Association*, 96, 1458-1468.

**2.**
Gelfand, A.E. and Kottas, A. (2001). Nonparametric Bayesian
modeling for stochastic order.

*Annals of the
Institute of Statistical Mathematics*, 53, 865-876.

**1.**
Kottas, A., Adamidis, K. and Loukas, S. (1999). Bivariate
distributions with Pearson Type VII conditionals.

*Annals of
the Institute of Statistical Mathematics*, 51, 331-344.

### Refereed proceedings papers

Viswanath, K., Obraczka, K., Kottas, A. and Sanso, B. (2006).
"A Statistical Equivalent Model for Random Waypoint Mobility: A Case
Study"

*
Proceedings of Symposium on Performance Evaluation of Computer and
Telecommunication Systems (SPECTS) 06*, July 31 -- August 2, 2006,
Calgary, Canada.

Kottas, A. (2006).
"Dirichlet Process Mixtures of Beta Distributions, with Applications to
Density and Intensity Estimation"

*Proceedings of the Workshop on Learning with Nonparametric
Bayesian Methods*, 23rd International Conference on Machine
Learning, June 2006, Pittsburgh, PA.

### Other publications

Kottas, A. (2018). Invited Discussion of
``Nonparametric Bayesian Inference in Applications'' by
Peter Mueller, Fernando A. Quintana and Garritt L. Page,
*Statistical Methods and Applications*, 27, pp. 219-225.

Kottas, A., DeYoreo, M. and Poynor, V. (2013).
Contributed Discussion of
``Bayesian Nonparametric Inference -- Why and How'' by
Peter Mueller and Riten Mitra, *Bayesian Analysis*, 8,
pp. 338-341.

Kottas, A. (2009). Review for book "Statistical Challenges in
Modern Astronomy IV" (G. Joseph Babu and Eric D. Feigelson eds.)
*Journal of the American Statistical Association*,
104, 418-419.

Kottas, A., Krnjajic, M. and Taddy, M. (2007).
``Model-based approaches to nonparametric
Bayesian quantile regression''

Proceedings of the *2007 Joint Statistical Meetings*,
IMS, pp. 1137-1148.

Kottas, A. (2007). "Survival Analysis, Nonparametric"
*Encyclopedia of Statistics in Quality and Reliability*
Ruggeri, F., Kenett, R. and Faltin, F.W. (eds). John Wiley &
Sons Ltd, Chichester, UK, pp. 1958-1962.

Morris, R.D., Kottas, A., Furfaro, R., Taddy, M.
and Ganapol, B. (2007). "An Analysis of the Uncertainties in Radiative
Transfer Models Used in Remote Sensed Data Product Generation"
Proceedings of the *NASA Science Technology Conference*, June 2007.

Kottas, A., Duan, J. and Gelfand, A.E. (2006).
"Bayesian Nonparametric Spatio-Temporal Models for Disease Incidence
Data"

Proceedings of the *2006 Joint Statistical Meetings*,
ASA Section on Bayesian Statistical Science, pp. 60-71.

Kottas, A., Mueller, P. and Quintana, F.A. (2003).
"A Nonparametric Bayesian Model for Multivariate Ordinal Data"

*Proceedings of the 2003 Joint Statistical Meetings*,
pp 2253-2257.

Bayarri, M.J., Berger, J.O., Higdon, D., Kennedy, M.C., Kottas,
A., Paulo, R., Sacks, J., Cafeo, J.A., Cavendish, J., Lin, C.H. and Tu,
J. (2002).
"A Framework for Validation of Computer Models"
* Proceedings of the Workshop on Foundations for V&V in the 21st
Century*, D. Pace and S. Stevenson (Editors). Society for Modeling
and Simulation International.

MacEachern, S.N., Kottas, A. and Gelfand, A.E. (2001).
"Spatial Nonparametric Bayesian Models"

* Proceedings of the 2001 Joint Statistical Meetings*.

thanos@soe.ucsc.edu
Last updated January 18, 2024