A NON‐GAUSSIAN FAMILY OF STATE‐SPACE MODELS WITH EXACT MARGINAL LIKELIHOOD

By Dani Gamerman, T. R. Santos, Glaura da Conceição Franco. 2013

71 citations recorded by the source corpus.

Subfields: Finance, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/bbd04b42a88e54aaffa16e6db589d4672940a776

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Science and Operations Research

1. Flávio B. Gonçalves
2. Dani Gamerman
3. Daniel M. McNeish

In Statistics and Probability

1. Flávio B. Gonçalves
2. Dani Gamerman
3. Daniel M. McNeish

Citations in the corpus

• Exact Bayesian inference in spatiotemporal Cox processes driven by multivariate Gaussian processes (2015, background): “otemporal model above can be proposed by adding a temporal dependence structure to λ∗ 0:T - this is particularly useful for prediction. One interesting possibility is the Markov structure proposed by Gamerman et al. (2013) (in a state-space model context) where λ ∗ 0 ∼ G(a0,b0), λ ∗ t|K1:t−1,λ ∗ t−1”