Published in Australian and New Zealand Journal of Statistics, 2025
Recommended citation: Menictas, M., Oates, C.J. and Wand, M.P., 2025. Online Semiparametric Regression via Sequential Monte Carlo. Australian and New Zealand Journal of Statistics, full publication details pending.
Published in Journal of Computational and Graphical Statistics, 2023
Recommended citation: Menictas, M., Di Credico, G. and Wand, M.P., 2023. Streamlined variational inference for linear mixed models with crossed random effects. Journal of Computational and Graphical Statistics, 32(1), pp.99-115.
Published in Contemporary Clinical Trials, 2021
Recommended citation: Battalio, S.L., Conroy, D.E., Dempsey, W., Liao, P., Menictas, M., Murphy, S., Nahum-Shani, I., Qian, T., Kumar, S. and Spring, B., 2021. Sense2Stop: a micro-randomized trial using wearable sensors to optimize a just-in-time-adaptive stress management intervention for smoking relapse prevention. Contemporary Clinical Trials, 109, p.106534.
Published in Statistical Modelling, 2021
Recommended citation: Menictas, M., Nolan, T.H., Simpson, D.G. and Wand, M.P., 2021. Streamlined variational inference for higher level group-specific curve models. Statistical Modelling, 21(6), pp.479-519.
Published in Journal of Machine Learning Research, 2020
Recommended citation: Nolan, T.H., Menictas, M. and Wand, M.P., 2020. Streamlined variational inference with higher level random effects. Journal of Machine Learning Research, 21(157), pp.1-62.
Published in mHealth in Addictions section for Current Addiction Reports, 2020
Recommended citation: Carpenter, S.M., Menictas, M., Nahum-Shani, I., Wetter, D.W. and Murphy, S.A., 2020. Developments in mobile health just-in-time adaptive interventions for addiction science. Current addiction reports, 7, pp.280-290.
Published in arXiv preprint, 2020
Recommended citation: Menictas, M., Tomkins, S. and Murphy, S.A., 2020. Streamlined Empirical Bayes Fitting of Linear Mixed Models in Mobile Health. arXiv preprint arXiv:2003.12881.
Published in The Biochemist, 2020
Recommended citation: Menictas, M., Rabbi, M., Klasnja, P. and Murphy, S., 2019. Artificial intelligence decision-making in mobile health. The biochemist, 41(5), pp.20-24.
Published in Doctoral dissertation, 2015
Recommended citation: Menictas, M., 2015. Variational inference for heteroscedastic and longitudinal regression models (Doctoral dissertation).
Published in Australian and New Zealand Journal of Statistics, 2015
Recommended citation: Menictas, M. and Wand, M.P., 2015. Variational inference for heteroscedastic semiparametric regression. Australian & New Zealand Journal of Statistics, 57(1), pp.119-138.
Published in Stat, 2013
Recommended citation: Menictas, M. and Wand, M.P., 2013. Variational inference for marginal longitudinal semiparametric regression. Stat, 2(1), pp.61-71.
Published in Journal of Tsunami Society International, 2010
Recommended citation: Groen, L., Joseph, A., Black, E., Menictas, M., Tam, W. and Gabor, M., 2010. Optimal location of Tsunami warning buoys and sea level monitoring stations in the Mediterranean Sea. Science of Tsunami Hazards.