Browsing by Author "Quintana Quintana, Fernando"
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- ItemA Bayesian Non-Parametric Dynamic AR Model for Multiple Time Series Analysis(2016) Nieto Barajas, L.; Quintana Quintana, Fernando
- ItemA Bayesian random partition model for sequential refinement and coagulation(2019) Zanini, C.T.P.; Muller, P.; Ji, Y.; Quintana Quintana, Fernando
- ItemA semiparametric Bayesian joint model for multiple mixed-type outcomes: an application to acute myocardial infarction(2018) Guglielmi, Alessandra; Ieva, Francesca; Paganoni, Anna Maria; Quintana Quintana, Fernando
- ItemA semiparametric Bayesian model for multiple monotonically increasing count sequences(2016) Leiva Yamaguchi, Valeria; Quintana Quintana, Fernando
- ItemA Simple Class of Bayesian Nonparametric Autoregression Models(2013) Di Lucca, Maria Anna; Guglielmi, Alessandra; Müller, Peter; Quintana Quintana, Fernando
- ItemA time series model for responses on the unit interval(2013) Jara, Alejandro; Nieto Barajas, L.; Quintana Quintana, Fernando
- ItemBayesian density estimation for compositional data using random Bernstein polynomials(2015) Barrientos, Andrés F.; Jara, Alejandro; Quintana Quintana, Fernando
- ItemBayesian inference for longitudinal data with non-parametric treatment effects(2014) Müller, Peter; Quintana Quintana, Fernando; Gary, L.; Rosner, Michael; Maitland, L.
- ItemBayesian nonparametric estimation of test equating functions with covariates(2015) González, J.; Barrientos, Andrés F.; Quintana Quintana, Fernando
- ItemBayesian Nonparametric Longitudinal Data Analysis(2016) Quintana Quintana, Fernando; Johnson, W.; Waetjen, L. B.; Gold, E.
- ItemBM-BC: a Bayesian method of base calling for Solexa sequence data(2012) Quintana Quintana, Fernando; Jara Weitzmann, Alejandro; Ji, Yuan; Mitra, Riten; Mueller, Peter; Liu, Ping; Lu, Yue; Liang, ShoudanAbstract Base calling is a critical step in the Solexa next-generation sequencing procedure. It compares the position-specific intensity measurements that reflect the signal strength of four possible bases (A, C, G, T) at each genomic position, and outputs estimates of the true sequences for short reads of DNA or RNA. We present a Bayesian method of base calling, BM-BC, for Solexa-GA sequencing data. The Bayesian method builds on a hierarchical model that accounts for three sources of noise in the data, which are known to affect the accuracy of the base calls: fading, phasing, and cross-talk between channels. We show that the new method improves the precision of base calling compared with currently leading methods. Furthermore, the proposed method provides a probability score that measures the confidence of each base call. This probability score can be used to estimate the false discovery rate of the base calling or to rank the precision of the estimated DNA sequences, which in turn can be useful for downstream analysis such as sequence alignment.
- ItemCalibrating covariate informed product partition models(2018) Page, Garritt L.; Quintana Quintana, Fernando
- ItemCluster-Specific Variable Selection for Product Partition Models(2015) Quintana Quintana, Fernando; Müller, Peter; Papoila, Ana Luisa
- ItemClustering and feature allocation(2015) Müller, Peter; Quintana Quintana, Fernando; Jara, Alejandro; Hanson, Tim
- ItemCluster‐specific variable selection for product partition models(2015) Quintana Quintana, Fernando; Mueller, Peter; Papoila, Ana Luisa
- ItemDefining Predictive Probability Functions for Species Sampling Models(2013) Lee, Jaeyong; Quintana Quintana, Fernando; Müller, Peter; Trippa, Lorenzo
- ItemDensity regression using repulsive distributions(2018) Quinlan, Jose J.; Page, Garritt L.; Quintana Quintana, Fernando
- ItemDependent Species Sampling Models for Spatial Density Estimation(2016) Jo, S.; Lee, J.; Muller, P.; Quintana Quintana, Fernando; Trippa, L.
- ItemDiscriminant Analysis for Longitudinal Data with Multiple Continuous Responses and Possibly Missing Data(2009) Marshall Rivera, Guillermo; Cruz Mesía, Rolando J. de la; Quintana Quintana, Fernando; Baron, Anna E.
- ItemEmpirical fragility curves of RC buildings in Chile using a cumulative link model(National Information Centre of Earthquake Engineering, 2017) Favier, Philomène; Quintana Quintana, Fernando; Magna Verdugo, Carolina Elena; Santa María Oyanedel, Hernán; Hube Ginestar, Matías Andrés; Llera Martin, Juan Carlos de laChile is known as one of the most seismic countries in the world showing approximately one event above magnitude 8 every ten years. Unexpected damage occurred in reinforced concrete (RC) buildings during the 2010 Mw 8.8 Maule earthquake. Calculating the risk for RC buildings to exceed a given damage state during potential future seismic events is thus of paramount importance. It is assumed that the risk can be calculated from a combination of an exposure model, an intensity hazard distribution, and the vulnerability definition of RC buildings. Construction of fragility curves is part of the process for vulnerability definition. We propose here in an innovative methodology to build empirical fragility curves with the collected data of Chilean RC buildings. After the 2010 Maule earthquake, a database of the damage states of Chilean RC buildings was built by the assessment of structural engineers from companies or municipalities. Damage was classified in five states: no damage, slight, moderate, severe and complete damage states. The database is composed of observations made in six Chilean cities exposed to different seismic intensity. An interpolation of a 2010 shakemap provides the intensity measure occurring at the location of each building. Different generalized linear models were tested and it was shown that the cumulative logit link model provides the best fit of fragility curves. Cumulative link models for ordinal data ensure that fragility curves do not cross. The number of buildings floors and the year of construction are considered as covariates of our model. A Bayesian approach is adopted to obtain estimates and distribution of the parameters describing the statistical model. The resulting fragility curves for RC buildings are compared with results available in the literature. The provided fragility curves for Chilean RC buildings is the major contribution of this study. Finally, the usability of the curves is investigated from a risk perspective, and the need of more information to improve the fitting procedure is discussed.