H. Nguyen, M. C. Ausín, Pedro Galeano (2020) Variational inference for high dimensional structured factor copulas, Computational Statistics and Data Analysis, 151, 107012
A. Virbickaite, M.C. Ausín, P. Galeano (2020) Copula stochastic volatility in oil returns: Approximate Bayesian computation with volatility prediction, Energy Economics , 92, 104961.
A. Virbickaite, H.F. Lopes, M.C. Ausín, P. Galeano (2019) Particle Learning for Bayesian Semi-Parametric Stochastic Volatility Model. Econometric Reviews, 38, 1007-1023.
H. Nguyen, M. C. Ausín, Pedro Galeano (2019) Parallel Bayesian inference for high dimensional dynamic factor copulas, Journal of Financial Econometrics, 17, 118-151.
A. Sarhadi, M.C. Ausín, M.P. Wiper, D. Touma and N.S. Diffenbaugh (2018). Multi-dimensional risk in a non-stationary climate: joint probability of increasingly severe warm and dry conditions. Science Advances, vol 4, no. 11.
M. Gómez, M.C. Ausín, M.C. Domínguez, (2018) Vine copula models for predicting water flow discharge at King George Island, Antarctica. Stochastic Environmental Research and Risk Assessment, 32, 2787–2807.
J.A. Carnicero, M.C. Ausín, M.P. Wiper (2018) Density estimation of circular data with Bernstein polynomials. Hacettepe Journal of Mathematics and Statistics, 47, 273-286.
M. Gómez, M.C. Ausín, M.C. Domínguez, (2017) Seasonal copula models for the analysis of glacier discharge at King George Island, Antarctica. Stochastic Environmental Research and Risk Assessment, 31, 1107-1121.
A. Sarhadi, M. C. Ausín, M. P. Wiper, (2016) A New Time-varying Concept of Risk in a Changing Climate. Nature Scientific Reports, 6, Article number: 35755.
A. Sarhadi, D. H. Burn, M. C. Ausín, M. P. Wiper (2016) Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula. Water Resources Research, 52, 2327–2349.
A. Virbickaite, M.C. Ausín, and P. Galeano (2016) A Bayesian Non-Parametric Approach to Asymmetric Dynamic Conditional Correlation Model with Application to Portfolio Selection. Computational Statistics and Data Analysis, 100, 814-829.
G. Núñez-Antonio, M.C. Ausín and M. P. Wiper (2015) Bayesian nonparametric models of circular variables based on Dirichlet process mixtures of normal distributions. Journal of Agricultural, Biological, and Environmental Statistics, 20, 47-64.
A. Virbickaite, M.C. Ausín, and P. Galeano (2015) Bayesian inference methods for univariate and multivariate GARCH models: a survey. Journal of Economic Surveys, 29, 76-96.
M. C. Ausín (2015). Markov Chain Monte Carlo, Introduction. Wiley StatsRef: Statistics Reference Online. 1–10. Update based on original article by Michael Wiper, Wiley StatsRef: Statistics Reference Online, © 2014, John Wiley & Sons, Ltd.
M.C. Ausín, P. Galeano and P. Ghosh (2014) A semiparametric Bayesian approach to the analysis of financial time series with applications to Value at Risk estimation. European Journal of Operational Research, 232, 350-358.
J.A. Carnicero, M.C. Ausín and M.P. Wiper (2013) Non-parametric copulas for circular-linear and circular-circular data: an application to wind directions. Stochastic Environmental Research and Risk Assessment, 27, 1991-2002.
M. C. Ausín, J.M. Vilar, R. Cao and C. González-Fragueiro (2011). Bayesian analysis of aggregate loss models. Mathematical Finance, 21, 257-279.
M. C. Ausín, M. A. Gómez-Villegas, B. González-Pérez, M. T. Rodríguez-Bernal and L. Sanz (2011). Bayesian analysis of multiple hypothesis testing with applications to microarray experiments. Communications in Statistics, 40, 2276–2291.
P. Galeano and M. C. Ausín (2010). The Gaussian Mixture Dynamic Conditional Correlation Model: Parameter Estimation, Value at Risk calculation and portfolio selection. Journal of Business and Economic Statistics, 28, 559 – 571.
M. C. Ausín and H. F. Lopes (2010). Bayesian prediction of risk measurements using copulas. Rethinking Risk Measurement and Reporting. Volume II. Klaus Böcker (ed.) Risk Books: London. pp. 31 - 67.
M. C. Ausín and H. Lopes (2010). Time-varying joint distribution through copulas. Computational Statistics and Data Analysis, 54, 2383-2399.
M. C. Ausín, M. P. Wiper and R. E. Lillo (2009). Bayesian estimation of finite time ruin probabilities. Applied Stochastic Models in Business and Industry, 25, 787-805.
J.M. Vilar, R. Cao, M. C. Ausín and C. González-Fragueiro (2009). Nonparametric analysis of aggregate loss models. Journal of Applied Statistics, 36, 149 - 166.
M. C. Ausín, M. P. Wiper and R. E. Lillo (2008). Bayesian prediction of the transient behaviour and busy period in short- and longtailed GI/G/1 queueing systems. Computational Statistics and Data Analysis, 52, 1615 - 1635.
M. C. Ausín and H. Lopes (2007). Bayesian estimation of ruin probabilities with heterogeneous and heavy-tailed insurance claim size distribution. Australian and New Zealand Journal of Statistics, 49, 1 - 20.
M. C. Ausín, R. E. Lillo and M. P. Wiper (2007). Bayesian control of the number of servers in a GI/M/c queueing system. Journal of Statistical Planning and Inference, 137, 3043 - 3057.
M. C. Ausín and P. Galeano (2007). Bayesian estimation of the Gaussian mixture GARCH model. Computational Statistics and Data Analysis, 51, 2636-2652.
M. C. Ausín (2007). Queues in Reliability. Encyclopedia of Statistics in Quality and Reliability. Wiley: Chichester, England. pp. 1550 - 1554.
M. C. Ausín (2007). An introduction to quadrature and other numerical integration techniques. Encyclopedia of Statistics in Quality and Reliability. Wiley: Chichester, England. pp. 1521 - 1526.
M. C. Ausín, M. P. Wiper and R. E. Lillo (2004) Bayesian estimation for the M/G/1 queue using a phase type approximation. Journal of Statistical Planning and Inference, 118, 83-101.
M. C. Ausín, R. E. Lillo, M. P. Wiper and F. Ruggeri (2003) Modeling of Hospital Bed Occupancy Times using a Mixed Generalized Erlang Distribution. Bayesian Statistics 7. Oxford University Press. pp. 443-451.