14 citations · 37 across the 20 of their papers we have counts for
7 papers · 1 filter
Bayesian sequential data assimilation for COVID-19 forecasting
Maria L. Daza-Torres, Marcos A. Capistrán, Antonio Capella +1
We introduce a Bayesian sequential data assimilation method for COVID-19 forecasting. It is assumed that suitable transmission, epidemic and observation models are available and pr…
A simulation study to compare 210Pb dating data analyses
Marco A Aquino-López, Nicole K. Sanderson, Maarten Blaauw +4
The increasing interest in understanding anthropogenic impacts on the environment have led to a considerable number of studies focusing on sedimentary records for the last 1…
Systematic statistical analysis of microbial data from dilution series
J Andrés Christen, Al Parker
In microbial studies, samples are often treated under different experimental conditions and then tested for microbial survival. A technique, dating back to the 1880's, consists of…
Modeling Oral Glucose Tolerance Test (OGTT) data and its Bayesian Inverse Problem
Nicolás Kuschinski, J. Andrés Christen, Adriana Monroy +1
One common way to test for diabetes is the Oral Glucose Tolerance Test or OGTT. Most common methods for the analysis of the data on this test are wasteful of much of the informatio…
An analysis of the interaction between influenza and respiratory syncytial virus based on acute respiratory infection records
Yendry N. Arguedas-Flatts, Marcos A. Capistrán, J. Andrés Christen +1
Under the hypothesis that both influenza and respiratory syncytial virus (RSV) are the two leading causes of acute respiratory infections (ARI), in this paper we have used a standa…
Towards Uncertainty Quantification and Inference in the stochastic SIR Epidemic Model
Marcos A. Capistrán, J. Andrés Christen, Jorge X. Velasco-Hernández
In this paper we introduce a novel method to conduct inference with models defined through a continuous-time Markov process, and we apply these results to a classical stochastic SI…
A Generic Multivariate Distribution for Counting Data
Marcos Capistrán, J. Andrés Christen
Motivated by the need, in some Bayesian likelihood free inference problems, of imputing a multivariate counting distribution based on its vector of means and variance-covariance ma…