Bruno Sansó

发表

Bayesian non-parametric modeling for integro-difference equations

Athanasios Kottas, Robert Richardson, Bruno Sansó, 2018, Stat. Comput..

30 Comparison of competing parametric survival models — a bayesian perspective

Keith R. Abrams, Bruno Sansó, 1997 .

Statistical calibration of climate system properties

Chris E. Forest, Bruno Sansó, B. Sansó, 2009 .

Nonparametric Bayesian Modeling and Estimation for Renewal Processes

Athanasios Kottas, Bruno Sansó, Sai Xiao, 2020, Technometrics.

Gaussian Process Modeling of Derivative Curves

David Higdon, Katrin Heitmann, Herbert K. H. Lee, 2013, Technometrics.

Flexible integro-difference equation modeling for spatio-temporal data

Athanasios Kottas, Robert Richardson, Bruno Sansó, 2017, Comput. Stat. Data Anal..

Joint projections of temperature and precipitation change from multiple climate models: a hierarchical Bayesian approach

Bruno Sansó, Claudia Tebaldi, C. Tebaldi, 2009 .

Spatially Varying Autoregressive Processes

Alexandra M. Schmidt, Bruno Sansó, Aline A. Nobre, 2011, Technometrics.

Comments on: A general science-based framework for dynamical spatio-temporal models

Bruno Sansó, 2010 .

On the robustness of the intrinsic Bayes factor for nested models

Luis R. Pericchi, Bruno Sansó, Elías Moreno, 1996 .

Redesigning a Network of Rainfall Stations

Peter Müller, Bruno Sansó, Peter Müller, 1999 .

Lithologic characterization of a reservoir using continuous-wavelet transforms

Reinaldo J. Michelena, Bruno Sansó, Giselle Alvarez, 2003, IEEE Trans. Geosci. Remote. Sens..

Multi-scale shotgun stochastic search for large spatial datasets

Bruno Sansó, Daniel Kirsner, B. Sansó, 2020, Comput. Stat. Data Anal..

BASS: An R Package for Fitting and Performing Sensitivity Analysis of Bayesian Adaptive Spline Surfaces

Bruno Sansó, Devin Francom, B. Sansó, 2020, Journal of Statistical Software.

Statistical Equivalent Models for Computer Simulators with an Application to the Random Waypoint Mobility Model

Katia Obraczka, Athanasios Kottas, Bruno Sansó, 2007, Simul..

Comparing Emulation Methods for Computer Models with High Dimensional Output

James R. Gattiker, Bruno Sansó, Devin Francom, 2021 .

Distributed nearest-neighbor Gaussian processes

Bruno Sansó, Isabelle Grenier, B. Sansó, 2021 .

Spatio‐temporal variability of ocean temperature in the Portugal Current System

Bruno Sansó, B. Sansó, R. T. Lemos, 2006 .

A spatiotemporal model for Mexico City ozone levels

Gabriel Huerta, Bruno Sansó, Jonathan R. Stroud, 2004 .

Meta-analysis of Heterogeneously Reported Study Results: A Bayesian Approach

Keith R. Abrams, Paul C. Lambert, Bruno Sansó, 2000 .

Dynamic Models for Spatio-Temporal Data

Bruno Sansó, Jonathan R. Stroud, Peter Müller, 2007 .

Advances in the Design of Gaussian Processes as Surrogate Models for Computer Experiments

J. Andrés Christen, Bruno Sansó, B. Sansó, 2008 .

A Nonstationary Multisite Model for Rainfall

Bruno Sansó, Lelys Guenni, B. Sansó, 2000 .

Hierarchical Bayesian modelling of wind and sea surface temperature from the Portuguese coast

Bruno Sansó, Filipe Duarte Santos, B. Sansó, 2010 .

Biological communities in San Francisco Bay track large‐scale climate forcing over the North Pacific

Monika Winder, Thomas M. Powell, John L. Largier, 2010 .

Comparing and Blending Regional Climate Model Predictions for the American Southwest

Dorit Hammerling, Andrew O. Finley, Paul L. Delamater, 2011 .

Inference for a Proton Accelerator Using Convolution Models

David Higdon, Bruno Sansó, Herbert K. H. Lee, 2008 .

Fast inference for statistical inverse problems

Matt Taddy, Bruno Sansó, Herbert K. H. Lee, 2009 .

Inferring particle distribution in a proton accelerator experiment

David Higdon, Bruno Sansó, Herbert K. H. Lee, 2006 .

A Bayesian approach to compare observed rainfall data to deterministic simulations

Bruno Sansó, B. Sansó, Lelys Guenni, 2004 .

Posterior Cumulant Relationships in Bayesian Inference Involving the Exponential Family

Luis R. Pericchi, Bruno Sansó, Adrian F. M. Smith, 1993 .

Time-varying models for extreme values

Gabriel Huerta, Bruno Sansó, B. Sansó, 2007, Environmental and Ecological Statistics.

Conditionally linear models for non-homogeneous spatial random fields

Bruno Sansó, B. Sansó, R. T. Lemos, 2012 .

Statistical science: contributions to the Administration's research priority on climate change

Noel A Cressie, Douglas W. Nychka, Stephan R. Sain, 2014 .