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Incorporating Parameter Estimability Into Model Selection

Jake M. Ferguson, Mark L. Taper, Rosana Zenil-Ferguson, Marie Jasieniuk, Bruce D. Maxwell
2019 Frontiers in Ecology and Evolution  
for both the number of parameters and their informational complexity.  ...  performance was evaluated using the frequency of selecting the generating model, the frequency of selecting the model with the best predictive ability, and the frequency of selecting the model with the minimum Kullback-Leibler  ...  Boik, Mark Greenwood, Steve Cherry, Subhash Lele, Jose Ponciano, Taal Levi, Kristen Sauby, and Robert Holt for comments on earlier drafts of this work.  ... 
doi:10.3389/fevo.2019.00427 fatcat:chnrsncronfq5jwlzrktzdixsi

Low Vitamin D Status and Influenza Vaccination Rates are Positive Predictors of Early Covid-19 Related Deaths in Europe – A Modeling Approach

Harald Walach, Rainer Johannes Klement
2021 Zenodo  
using generalized linear models: Percent test-standardized number of SARS-CoV-2-cases, population size, life expectancy, severity of governmental responses, influenza-vaccination coverage and vitamin  ...  Conclusion: Adequate vitamin D levels are important, while − contrary to current opinion − flu-vaccination in the elderly is a putative aggravating factor of Covid-19 related deaths.  ...  Model adequacy was measured by R 2 , the proportion of variance explained by the predictors; for the GLMs a Kullback-Leibler divergence-based R 2 measure was used 13 .  ... 
doi:10.5281/zenodo.4680691 fatcat:ol4pqlm2onek7ekwzorroz4rma

Temporal association of neuropsychological test performance using unsupervised learning reveals a distinct signature of Alzheimer's disease status

Prajakta S. Joshi, Megan Heydari, Shruti Kannan, Ting Fang Alvin Ang, Qiuyuan Qin, Xue Liu, Jesse Mez, Sherral Devine, Rhoda Au, Vijaya B. Kolachalama
2019 Alzheimer s & Dementia Translational Research & Clinical Interventions  
This approach could be a viable option for early AD screening in clinical practice and clinical trials.  ...  Neuropsychological (NP) testing is an attractive modality for screening early evidence of AD.  ...  Kullback-Leibler (KL) divergence distribution plots on (A) FHS and (B) NACC data sets.  ... 
doi:10.1016/j.trci.2019.11.006 pmid:31921970 pmcid:PMC6944730 fatcat:5in2hkgeijcs5lhn5lmydijw7u

1 Generalities [chapter]

2019 Non-Extensive Entropy Econometrics for Low Frequency Series  
On one side, Shannon-Jaynes-Kullback-Leibler-based approaches are currently used for modelling economic phenomena competitively with classical econometrics.  ...  Following what has been said above, this monograph targets developing a robust approach generalizing Kullback-Leibler-Shannon entropy for solving inverse problems related to national account models in  ... 
doi:10.1515/9783110605914-003 fatcat:iqhlhaasnfbr5c52k7kemju544

Fast identification of optimal fascicle configurations from standard clinical diffusion MRI using Akaike information criterion

Aymeric Stamm, Olivier Commowick, Patrick Perez, Christian Barillot
2014 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)  
Starting from a set of fitted models with increasing number of fascicles, we use Akaike information criterion to estimate the probability of each candidate model to be the best Kullback-Leibler model.  ...  In this paper, we aim at proposing a novel approach to identify such a configuration from clinical diffusion MRI where only few diffusion images can be acquired and time is of the essence.  ...  Starting with a candidate set, we search for the best Kullback-Leibler (KL) MCM (i.e., at minimal KL divergence to the true unknown diffusion model) as a combination of the candidate models.  ... 
doi:10.1109/isbi.2014.6867853 dblp:conf/isbi/StammCPB14 fatcat:hnxigoe2yjherlqnqlhm2f6udm

Maximum Regularized Likelihood Estimators: A General Prediction Theory and Applications [article]

Rui Zhuang, Johannes Lederer
2018 arXiv   pre-print
In this paper, we derive guarantees for MRLEs in Kullback-Leibler divergence, a general measure of prediction accuracy.  ...  We assume only that the densities have a convex parametrization and that the regularization is definite and positive homogenous.  ...  We also thank Jacob Bien, Roy Han, Joseph Salmon, Noah Simon, and Yizhe Zhu for valuable input.  ... 
arXiv:1710.02950v2 fatcat:rs3xsgcgzjezjbkxx7kgexfdsi

Developing a Thermal Comfort Index for Vegetated Open Spaces in Cities of Arid Zones

M. Angélica Ruiz, Erica N. Correa
2014 Energy Procedia  
The theory of Akaike's information is used as criterion to model selection.  ...  For this, there were campaigns monitoring of microclimatic parameters and field surveys about the real sensation of the people on a pedestrian street of Mendoza Metropolitan Area (MMA) in both winter and  ...  ., Kullback-Leibler information) [26] . The AIC is not a test in any sense: no single hypothesis is made to be the null, no arbitrary a level is set, and no notion of significance is needed.  ... 
doi:10.1016/j.egypro.2015.06.056 fatcat:pb7dhtdannadpidseecqajbifa

Segmenting accelerometer data from daily life with unsupervised machine learning

Dafne van Kuppevelt, Joe Heywood, Mark Hamer, Séverine Sabia, Emla Fitzsimons, Vincent van Hees, Maciej S. Buchowski
2019 PLoS ONE  
To address these limitations, we present a data-driven approach for segmenting and clustering the accelerometer data using unsupervised machine learning.  ...  that can be gained for a variety of raw data metrics.  ...  To evaluate that a subsample can generalize to a larger population we tested the reproducibility.  ... 
doi:10.1371/journal.pone.0208692 pmid:30625153 pmcid:PMC6326431 fatcat:b5cboupmrbd2zocye6qr6ws75u

BIITE: A Tool to Determine HLA Class II Epitopes from T Cell ELISpot Data

Lies Boelen, Patrick K. O'Neill, Kathryn J. Quigley, Catherine J. Reynolds, Bernard Maillere, John H. Robinson, Ganjana Lertmemongkolchai, Daniel M. Altmann, Rosemary J. Boyton, Becca Asquith, Bjoern Peters
2016 PLoS Computational Biology  
We present a Bayesian approach to solve this problem and have implemented it for use with the statistical language R under the BIITE moniker.  ...  Furthermore, users can enter additional information they might have (from literature or other experiments) in the form of prior information.  ...  Acknowledgments We have used the high performance cluster at Imperial College for this project.  ... 
doi:10.1371/journal.pcbi.1004796 pmid:26953935 pmcid:PMC4783075 fatcat:ulquq42rfvbphkjzqq33ksz5gm

Segmenting accelerometer data from daily life with unsupervised machine learning [article]

Dafne Erica van Kuppevelt, Joe Heywood, Mark Hamer, Séverine Sabia, Emla Fitzsimons, Vincent van Hees
2018 biorxiv/medrxiv   pre-print
information that can be gained for a variety of raw data metrics.  ...  A cut-points approach was used as comparison.  ...  To evaluate that a subsample can generalize to a larger population we tested the reproducibility.  ... 
doi:10.1101/263046 fatcat:3kzqerr5bzbxpgu27rdaq74p3y

A Study of the Simulated Evolution of the Spectral Sensitivity of Visual Agent Receptors

Achim Liese, Daniel Polani, Thomas Uthmann
2001 Artificial Life  
In this article we study a model for the evolution of the spectral sensitivity of visual receptors for agents in a continuous virtual environment.  ...  The properties of the evolved sensors are analyzed for different scenarios.  ...  Thus the resulting sampling error for the experimental distribution p ev causes the significant outliers in the value for the Kullback-Leibler distance.  ... 
doi:10.1162/106454601753138961 pmid:11580876 fatcat:q5x7odgrufcojc7xmsvdfyxrla

A brief introduction to mixed effects modelling and multi-model inference in ecology

Xavier A. Harrison, Lynda Donaldson, Maria Eugenia Correa-Cano, Julian Evans, David N. Fisher, Cecily E.D. Goodwin, Beth S. Robinson, David J. Hodgson, Richard Inger
2018 PeerJ  
Whilst LMMs offer a flexible approach to modelling a broad range of data types, ecological data are often complex and require complex model structures, and the fitting and interpretation of such models  ...  We offer practical solutions and direct the reader to key references that provide further technical detail for those seeking a deeper understanding.  ...  ACKNOWLEDGEMENTS This paper is the result of a University of Exeter workshop on best practice for the application of mixed effects models and model selection in ecological studies.  ... 
doi:10.7717/peerj.4794 pmid:29844961 pmcid:PMC5970551 fatcat:6de6rwt5sfbd3c2o7wojglaa3m

INFORMATION THEORETIC REGRESSION METHODS [chapter]

Ehsan S. Soofi
1997 Advances in Econometrics  
Pesaran (1987) showed a similar result for the case when the distribution of y under M k is lognormal. 33 MDI Tests Information theoretic testing of linear hypotheses regarding a regression coefficient  ...  Discrimination Information The most widely known information theoretic measure of discrepancy between two distributions is the Kullback-Leibler discrimination information function = -H[f(x) ] -E f {log  ...  GENERAL INSTRUCTIONS FOR COMPLETING SF 298 The ReDOrt Documentation Page (RDP) is used in announcing and cataloging reports.  ... 
doi:10.1108/s0731-9053(1997)0000012004 fatcat:ansgqbrkw5aazawl2hcv3ciz5i

Diffusion Tensor Field Registration in the Presence of Uncertainty [chapter]

Mustafa Okan Irfanoglu, Cheng Guan Koay, Sinisa Pajevic, Raghu Machiraju, Peter J. Basser
2009 Lecture Notes in Computer Science  
The dissimilarity between distributions of tensors in two different voxels is computed using the Kullback-Leibler divergence to drive a deformable registration process, which is not only affected by principal  ...  We propose a novel method for deformable tensor-to-tensor registration of Diffusion Tensor Imaging (DTI) data.  ...  Registration Framework The Kullback-Leibler (KL) divergence dissimilarity for tensor-variate Gaussian distributions is used as a voxelwise dissimilarity metric in a hierarchical regis tration framework  ... 
doi:10.1007/978-3-642-04268-3_23 fatcat:hzfxac3pajak3cllfnbjezal7q

Performance of variable selection methods in predicting language proficiency using language learning proficiency

Johannah Jamalul Kiram, Jumat Sulaiman, Suyansah Swanto, Wardatul Akmam Din
2015 Applied Mathematical Sciences  
sat for the Malaysian English University Test (MUET).  ...  Two hundred thirty pre-university students of UMS participated by answering a self-report questionnaire called the Strategy Inventory for Language Learning (SILL), a background questionnaire, and then  ...  Introduced by Hirotugu Akaike [6] , it was based on Kullback-Leibler information [7, 8] where Akaike discovered a valid connection between Kullback-Leibler information and likelihood theory.  ... 
doi:10.12988/ams.2015.411989 fatcat:4a4sczyrxjc3bd2dajk5zmou7y
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