Search Results - "Bouranis, Lampros"

Statistical Network Analysis with Bergm by Caimo, Alberto, Bouranis, Lampros, Krause, Robert, Friel, Nial

“…Recent advances in computational methods for intractable models have made network data increasingly amenable to statistical analysis. Exponential random graph…”
Get full text

The Effect of Granular Commercial Fertilizers Containing Elemental Sulfur on Wheat Yield under Mediterranean Conditions by Bouranis, Dimitris L, Gasparatos, Dionisios, Zechmann, Bernd, Bouranis, Lampros D, Chorianopoulou, Styliani N

“…The demand to develop fertilizers with higher sulfur use efficiency has intensified over the last decade, since sulfur deficiency in crops has become more…”
Get full text

A Power Function Based Approach for the Assessment of the Sulfate Deprivation Impact on Nutrient Allocation in Young Maize Plants by Bouranis, Dimitris L., Chorianopoulou, Styliani N., Bouranis, Lampros D.

“…Thirteen-day-old maize (Zea mays L.) plants were exposed hydroponically to sulfur (S)-deprivation and their nutritional status was monitored for ten days…”
Get full text

Modeling the Trends of Nutrient Concentration Dynamics in S-Deprived Young Maize Plants by Bouranis, Dimitris L, Chorianopoulou, Styliani N, Bouranis, Lampros D

“…Sulfate deprivation altered nutrient concentrations in both shoot and root of young maize (Zea mays L.) plants. A model is presented to that simulates the…”
Get full text

Bernadette: Bayesian Inference and Model Selection for Stochastic Epidemics in R by Bouranis, Lampros

Get full text

Bayesian Model Selection for Exponential Random Graph Models via Adjusted Pseudolikelihoods by Bouranis, Lampros, Friel, Nial, Maire, Florian

“…Models with intractable likelihood functions arise in areas including network analysis and spatial statistics, especially those involving Gibbs random fields…”
Get full text

Efficient Bayesian inference for exponential random graph models by correcting the pseudo-posterior distribution by Bouranis, Lampros, Friel, Nial, Maire, Florian

“…•The ERG likelihood is approximated by a pseudolikelihood function.•Such an approximation results in flawed Bayesian inference.•Our methodology calibrates the…”
Get full text

Model comparison for Gibbs random fields using noisy reversible jump Markov chain Monte Carlo by Bouranis, Lampros, Friel, Nial, Maire, Florian

“…The reversible jump Markov chain Monte Carlo (RJMCMC) method offers an across-model simulation approach for Bayesian estimation and model comparison, by…”
Get full text

Bayesian analysis of diffusion-driven multi-type epidemic models with application to COVID-19 by Bouranis, Lampros, Demiris, Nikolaos, Kalogeropoulos, Konstantinos, Ntzoufras, Ioannis

“…We consider a flexible Bayesian evidence synthesis approach to model the age-specific transmission dynamics of COVID-19 based on daily mortality counts. The…”
Get full text

Statistical Network Analysis with Bergm by Caimo, Alberto, Bouranis, Lampros, Krause, Robert, Friel, Nial

“…Recent advances in computational methods for intractable models have made network data increasingly amenable to statistical analysis. Exponential random graph…”
Get full text

Model comparison for Gibbs random fields using noisy reversible jump Markov chain Monte Carlo by Bouranis, Lampros, Friel, Nial, Maire, Florian

“…Computational Statistics and Data Analysis 128 (2018) 221-241 The reversible jump Markov chain Monte Carlo (RJMCMC) method offers an across-model simulation…”
Get full text

Bayesian model selection for exponential random graph models via adjusted pseudolikelihoods by Bouranis, Lampros, Friel, Nial, Maire, Florian

“…Journal of Computational and Graphical Statistics 27:3 (2018) 516-528 Models with intractable likelihood functions arise in areas including network analysis…”
Get full text

Efficient Bayesian inference for exponential random graph models by correcting the pseudo-posterior distribution by Bouranis, Lampros, Friel, Nial, Maire, Florian

“…Soc. Networks 50 (2017) 98-108 Exponential random graph models are an important tool in the statistical analysis of data. However, Bayesian parameter…”
Get full text