Bayesian multivariate linear regression with application to change point models in hydrometeorological variables

By Ousmane Seidou, J. Asselin, Taha B. M. J. Ouarda. 2007

60 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Ocean Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/70b7f39f762d46783c2f5cdfba2ca10426b895b6

How researchers see this paper

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

In Global and Planetary Change

1. James Merleau
2. Luc Perreault
3. Guillaume Évin

In Statistics and Probability

1. James Merleau
2. Pengyu Liu
3. Luc Perreault
4. I. Macneill
5. Guillaume Évin
6. Stergios B. Fotopoulos
7. Venkata K. Jandhyala
8. M. Ernst

Citations in the corpus

• Two‐component mixtures of normal, gamma, and Gumbel distributions for hydrological applications (2011, background): “In hydrology, this problem has received considerable attention in recent years [Perreault et al., 2000b; Thyer and Kuczera, 2000; Fortin et al., 2004; Kehagias, 2004; Seidou et al., 2007; Jandhyala et al., 2009].”
• Inference for single and multiple change‐points in time series (2013, background): “…2000b), change in the mean vector of a multivariate normal distribution (Perreault et al., 2000c), single change in the parameters of a multiple LR model (Seidou et al., 2007) and also the more complex case of estimating multiple change-points (Fearnhead, 2005, 2006; Seidou and Ouarda, 2007).”