S. Martino

发表

Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations

H. Rue, S. Martino, N. Chopin, 2009 .

Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations

H. Rue, S. Martino, N. Chopin, 2009 .

Approximate Bayesian Inference for Latent Gaussian Models

S. Martino, 2007 .

Approximate Bayesian inference for hierarchical Gaussian Markov random field models

H. Rue, S. Martino, 2007 .

Approximate Bayesian Inference in Spatial Generalized Linear Mixed Models

H. Rue, S. Martino, J. Eidsvik, 2008 .

Approximate Bayesian Inference for Survival Models

H. Rue, S. Martino, R. Akerkar, 2010 .

Case studies in Bayesian computation using INLA

Håvard Rue, Sara Martino, H. Rue, 2010 .

Norges Teknisk-naturvitenskapelige Universitet Implementing Approximate Bayesian Inference Using Integrated Nested Laplace Approximation: a Manual for the Inla Program Implementing Approximate Bayesian Inference Using Integrated Nested Laplace Approximation: a Manual for the Inla Program

Håvard Rue, Sara Martino, H. Rue, 2022 .

for Survival Analysis using Integrated Nested Laplace Approximations

S. Martino, R. Akerkar, 2010 .

Estimation of a non-stationary model for annual precipitation in southern Norway using replicates of the spatial field

S. Martino, F. Lindgren, I. Steinsland, 2014, 1412.2798.

Spatio-temporal modelling of $\text{PM}_{10}$ daily concentrations in Italy using the SPDE approach

S. Martino, M. Cameletti, G. Cattani, 2020, 2009.10476.

Norges Teknisk-naturvitenskapelige Universitet Approximate Bayesian Inference for Multivariate Stochastic Volatility Models Approximate Bayesian Inference for Multivariate Stochastic Volatility Models

S. Martino, 2022 .

NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET Approximate Inference for Hierarchical Gaussian Markov Random Fields Models by H̊avard Rue &

S. Martino, 2005 .

Seasonal distribution of an opportunistic apex predator (Tursiops truncatus) in marine coastal habitats of the Western Mediterranean Sea

S. Martino, G. Jona-Lasinio, D. S. Pace, 2022, Frontiers in Marine Science.

Adjusting Posteriors from Composite and Misspeciﬁed Likelihoods with Application to Spatial Extremes in R-INLA

Silius M. Vandeskog, S. Martino, R. Huser, 2022 .

Examining the extremal dependence structure of precipitation in Norway

Silius M. Vandeskog, S. Martino, 2020 .

Animal Models and Integrated Nested Laplace Approximations

Sara Martino, Ingelin Steinsland, S. Martino, 2013, G3: Genes, Genomes, Genetics.

Integrated Nested Laplace Approximations (INLA)

Andrea Riebler, Sara Martino, S. Martino, 2019, Wiley StatsRef: Statistics Reference Online.

Hierarchical analysis of spatially autocorrelated ecological data using integrated nested Laplace approximation

Håvard Rue, Julien Beguin, Sara Martino, 2012 .

Modelling short-term precipitation extremes with the blended generalised extreme value distribution

Haavard Rue, Sara Martino, Daniela Castro-Camilo, 2021 .

Modelling Sub-daily Precipitation Extremes with the Blended Generalised Extreme Value Distribution

Silius M. Vandeskog, H. Rue, S. Martino, 2021, Journal of Agricultural, Biological and Environmental Statistics.

Spatio-temporal modelling of PM10 daily concentrations in Italy using the SPDE approach

Michela Cameletti, Giorgio Cattani, Sara Martino, 2021 .

TEKNISK-NATURVITENSKAPELIGE UNIVERSITET Animal models and Integrated Nested Laplace Approximations by

S. Martino, I. Steinsland, H. Jensen, 2011 .

A joint Bayesian framework for missing data and measurement error using integrated nested Laplace approximations

S. Martino, S. Muff, Emma Sofie Skarstein, 2023, Biometrical journal. Biometrische Zeitschrift.

Bayesian spatial analysis of crash severity data with the INLA approach: Assessment of different identification constraints.

S. Martino, H. Baghishani, Leila Barmoudeh, 2022, Accident; analysis and prevention.

Fitting complex ecological point process models with integrated nested Laplace approximation

Justin M. J. Travis, Janine B. Illian, Sara Martino, 2013 .

A spatiotemporal analysis of NO2 concentrations during the Italian 2020 COVID‐19 lockdown

S. Martino, E. Pisoni, M. Cameletti, 2022, Environmetrics.

A spatiotemporal analysis of NO2 concentrations during the Italian 2020 COVID‐19 lockdown

Enrico Pisoni, Michela Cameletti, Giorgio Cattani, 2021, Environmetrics.

A Concrete Challenge for Territorial Governance in Europe

S. Martino, 2021 .

Norges Teknisk-naturvitenskapelige Universitet Estimating Stochastic Volatility Models Using Integrated Nested Laplace Approximations Estimating Stochastic Volatility Models Using Integrated Nested Laplace Approximations

Kjersti Aas, Håvard Rue, Sara Martino, 2022 .

Integration of presence‐only data from several sources: a case study on dolphins' spatial distribution

S. Martino, G. Jona Lasinio, D. S. Pace, 2021, Ecography.

Spatial Modelling of Temperature and Humidity using Systems of Stochastic Partial Differential Equations

Haavard Rue, Daniel Simpson, Sara Martino, 2013, 1307.1402.

Approximate Bayesian Inference for Latent Gaussian Models Using Integrated Nested Laplace Approximations

H. Rue, S. Martino, 2007 .

Fast spatial simulation of extreme high-resolution radar precipitation data using INLA

Silius M. Vandeskog, S. Martino, O. Bruland, 2023, 2307.11390.

Estimating stochastic volatility models using integrated nested Laplace approximations

H. Rue, S. Martino, K. Aas, 2011 .

Norges Teknisk-naturvitenskapelige Universitet Approximate Bayesian Inference for Survival Models Approximate Bayesian Inference for Survival Models

H. Rue, S. Martino, R. Akerkar, 2022 .

Modelling short-term precipitation extremes with the blended generalised extreme value distribution

Silius M. Vandeskog, S. Martino, H. Rue, 2021 .