Michela Cameletti
Statistics and Probability · 2012–2015
A researcher in the Science corpus: 4 papers; trusts 26 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 37 citations into it; #9,255 of 12,932 by trust here, #7,508 by citations
- Artificial Intelligence — 23 citations into it
- Economics and Econometrics — 23 citations into it
- Environmental Engineering — 23 citations into it; #2,180 of 5,479 by trust here, #2,867 by citations
- Probabilistic & Bayesian Methods — 8 citations into it
- Applied Mathematics — 7 citations into it
- Signal Processing — 7 citations into it
- Geography, Planning and Development — 5 citations into it
Whom Michela Cameletti trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Håvard Rue
- Julian Besag
- Finn Lindgren
- Christian P. Robert
- Edzer J. Pebesma
- Alan E. Gelfand
- David B. Dunson
- Leonhard Held
- Sara Martino
- L. Knorr‐Held
Who trusts Michela Cameletti overall
- Finn Lindgren
- Håvard Rue
- Marta Blangiardo
- Thiago G. Martins
- H. Bakka
- Yuzhe Yang
- David Bolin
- Daniel P. Simpson
- Luigi Lombardo
- Zijie Zheng
Papers from Michela Cameletti's perspective
Ordered by how strongly the researchers Michela Cameletti trusts endorse each paper. Same corpus, a different order for every researcher.
- Bayesian measures of model complexity and fit
- Spatial Interaction and the Statistical Analysis of Lattice Systems
- Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations
- Monte Carlo Statistical Methods
- Hierarchical Modeling and Analysis for Spatial Data
- BAYESIAN THEORY
- Statistics for Spatio-Temporal Data
- Gaussian Markov Random Fields: Theory and Applications
- An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach
- Sampling-Based Approaches to Calculating Marginal Densities
Their papers
- Spatial and Spatio-temporal Bayesian Models with R - INLA (2015) — 786 citations
- Spatial and spatio-temporal models with R-INLA. (2013) — 421 citations
- Spatial and spatio-temporal models with R-INLA. (2013) — 330 citations
- Spatio-temporal modeling of particulate matter concentration through the SPDE approach (2012) — 406 citations