A general sparse modeling approach for regression problems involving functional data

2017 ◽  
pp. 33-40
Author(s):  
Germán Aneiros ◽  
Philippe Vieu
Keyword(s):  
Functional Data ◽  
Sparse Modeling ◽  
Modeling Approach ◽  
Regression Problems

scholarly journals Disentangling key species interactions in diverse and heterogeneous communities: A Bayesian sparse modeling approach

2021 ◽  
Author(s):  
Christopher Weiss-Lehman ◽  
Chhaya M Werner ◽  
Catherine H Bowler ◽  
Lauren M Hallett ◽  
Margaret M Mayfield ◽  
...  
Keyword(s):  
Species Interactions ◽  
Predictive Accuracy ◽  
Bayesian Variable Selection ◽  
Model Parameters ◽  
Interaction Coefficients ◽  
Direct Role ◽  
Sparse Modeling ◽  
Modeling Approach ◽  
Key Species ◽  
Diverse Communities

Modeling species interactions in diverse communities traditionally requires a prohibitively large number of species-interaction coefficients, especially when considering environmental dependence of parameters. We implemented Bayesian variable selection via sparsity-inducing priors on non-linear species abundance models to determine which species-interactions should be retained and which can be represented as an average heterospecific interaction term, reducing the number of model parameters. We evaluated model performance using simulated communities, computing out-of-sample predictive accuracy and parameter recovery across different input sample sizes. We applied our method to a diverse empirical community, allowing us to disentangle the direct role of environmental gradients on species' intrinsic growth rates from indirect effects via competitive interactions. We also identified a few neighboring species from the diverse community that had non-generic interactions with our focal species. This sparse modeling approach facilitates exploration of species-interactions in diverse communities while maintaining a manageable number of parameters.

scholarly journals Sparse modeling approach to analytical continuation of imaginary-time quantum Monte Carlo data

2017 ◽  
Vol 95 (6) ◽  
Author(s):  
Junya Otsuki ◽  
Masayuki Ohzeki ◽  
Hiroshi Shinaoka ◽  
Kazuyoshi Yoshimi
Keyword(s):  
Monte Carlo ◽  
Quantum Monte Carlo ◽  
Analytical Continuation ◽  
Imaginary Time ◽  
Monte Carlo Data ◽  
Sparse Modeling ◽  
Modeling Approach ◽  
Time Quantum

scholarly journals Sparse modeling approach for identifying the dominant factors affecting situation-dependent hourly electricity demand

2020 ◽  
Vol 265 ◽  
pp. 114752
Author(s):  
Nanae Kaneko ◽  
Yu Fujimoto ◽  
Satoshi Kabe ◽  
Motonari Hayashida ◽  
Yasuhiro Hayashi
Keyword(s):  
Electricity Demand ◽  
Sparse Modeling ◽  
Factors Affecting ◽  
Modeling Approach

Prospective memory and working memory: A hierarchical modeling approach

2012 ◽  
Author(s):  
Nina R. Arnold ◽  
Ute J. Bayen ◽  
Rebekah E. Smith
Keyword(s):  
Working Memory ◽  
Prospective Memory ◽  
Hierarchical Modeling ◽  
Modeling Approach

Prospective Memory and Working Memory: A Hierarchical Modeling Approach

2012 ◽  
Author(s):  
Nina R. Arnold ◽  
Ute J. Bayen ◽  
Rebekah E. Smith
Keyword(s):  
Working Memory ◽  
Prospective Memory ◽  
Hierarchical Modeling ◽  
Modeling Approach
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