6 citations · 7 across the 7 of their papers we have counts for
10 papers
Stochastic EM Estimation and Inference for Zero-Inflated Beta-Binomial Mixed Models for Longitudinal Count Data
John Barrera, Ana Arribas-Gil, Dae-Jin Lee +1
Analyzing overdispersed, zero-inflated, longitudinal count data poses significant modeling and computational challenges, which standard count models (e.g., Poisson or negative bino…
A stochastic method to estimate a zero-inflated two-part mixed model for human microbiome data
John Barrera, Cristian Meza, Ana Arribas-Gil
Human microbiome studies based on genetic sequencing techniques produce compositional longitudinal data of the relative abundances of microbial taxa over time, allowing to understa…
Visualizing Outliers in High Dimensional Functional Data for Task fMRI data exploration
Yasser Aleman-Gomez, Ana Arribas-Gil, Manuel Desco +2
Task-based functional magnetic resonance imaging (task fMRI) is a non-invasive technique that allows identifying brain regions whose activity changes when individuals are asked to…
A time warping approach to multiple sequence alignment
Ana Arribas-Gil, Catherine Matias
We propose an approach for multiple sequence alignment (MSA) derived from the dynamic time warping viewpoint and recent techniques of curve synchronization developed in the context…
Bayesian Regression Analysis of Data with Random Effects Covariates from Nonlinear Longitudinal Measurements
Rolando De la Cruz, Cristian Meza, Ana Arribas-Gil +1
Joint models for a wide class of response variables and longitudinal measurements consist on a mixed-effects model to fit longitudinal trajectories whose random effects enter as co…
Shape Outlier Detection and Visualization for Functional Data: the Outliergram
Ana Arribas-Gil, Juan Romo
We propose a new method to visualize and detect shape outliers in samples of curves. In functional data analysis we observe curves defined over a given real interval and shape outl…
Pairwise Dynamic Time Warping for Event Data
Ana Arribas-Gil, Hans-Georg Müller
We introduce a new version of dynamic time warping for samples of observed event times that are modeled as time-warped intensity processes. Our approach is devel- oped within a fra…
Lasso-type estimators for Semiparametric Nonlinear Mixed-Effects Models Estimation
Ana Arribas-Gil, Karine Bertin, Cristian Meza +1
Parametric nonlinear mixed effects models (NLMEs) are now widely used in biometrical studies, especially in pharmacokinetics research and HIV dynamics models, due to, among other a…
A context dependent pair hidden Markov model for statistical alignment
Ana Arribas-Gil, Catherine Matias
This article proposes a novel approach to statistical alignment of nucleotide sequences by introducing a context dependent structure on the substitution process in the underlying e…
Parameter estimation in pair hidden Markov models
Ana Arribas-Gil, Elisabeth Gassiat, Catherine Matias
This paper deals with parameter estimation in pair hidden Markov models (pair-HMMs). We first provide a rigorous formalism for these models and discuss possible definitions of like…