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Concept-oriented model: Modeling and processing data using functions [article]

Alexandr Savinov
2019 arXiv   pre-print
It uses mathematical functions as first-class constructs for data representation and data processing as opposed to using exclusively sets in conventional set-oriented models.  ...  The main benefit of this model is that typical data processing tasks become simpler and more natural when using functions in comparison to adopting sets and set operations.  ...  Other models like the functional data model (FDM) distinguish between value sets and entity sets.  ... 
arXiv:1911.07225v1 fatcat:qzx5mlhhdrcfnatwvgdwrkvfba

View Modeling and Integration Using the Functional Data Model

S.B. Yao, V.E. Waddle, B. Housel
1982 IEEE Transactions on Software Engineering  
The system is based on a data model called the Functional Data Model (FDM), and on a transaction (or process) model which is specified via the Transaction Specification Language (TASL).  ...  The global description is then mapped into a structure which is compatible with the data model supported by the DBMS (view restructuring).  ...  THE FUNCTIONAL DATA MODEL The Functional Data Model consists of sets and functions between sets. The sets represent data values stored in the database.  ... 
doi:10.1109/tse.1982.235883 fatcat:r7wz4dl3orfpjmxuuhkcngnshu

Learning Models over Relational Data using Sparse Tensors and Functional Dependencies [article]

Mahmoud Abo Khamis and Hung Q. Ngo and XuanLong Nguyen and Dan Olteanu and Maximilian Schleich
2020 arXiv   pre-print
These integrated solutions are also a fertile ground of theoretically fundamental and challenging problems at the intersection of relational and statistical data models.  ...  the format of an external learning tool; and train the desired model using this tool.  ...  XN is supported in part by grants NSF CAREER DMS-1351362, NSF CNS-1409303 and the Margaret and Herman Sokol Faculty Award.  ... 
arXiv:1703.04780v5 fatcat:yrnjj77urvfrtmj2hllm2623si

Model-Based Clustering and Classification of Functional Data [article]

Faicel Chamroukhi, Hien D. Nguyen
2018 arXiv   pre-print
We review and present approaches for model-based clustering and classification of functional data.  ...  The presented models and algorithms are illustrated on real-world functional data analysis problems from several application area.  ...  The resulting models are better able to handle functional data structures and are referred to as functional mixture models.  ... 
arXiv:1803.00276v2 fatcat:phigorb7pfhu7bat5iywjgloyy

Spatial Functional Data Modeling of Plant Reflectances [article]

Philip A. White and Henry Frye and Michael F. Christensen and Alan E. Gelfand and John A. Silander Jr
2021 arXiv   pre-print
Wavelength responses for an individual leaf are viewed as a function of wavelength, leading to functional data modeling. Local environmental features become covariates.  ...  We implement out-of-sample validation to select a best model, discovering that the model features listed above are all informative for the functional data analysis.  ...  We thank Matthew Aiello-Lammens, Douglas Euston-Brown, Hayley Kilroy Mollmann, Cory Merow, Jasper Slingsby, Helga van der Merwe, and Adam Wilson for their contributions in the data collection and curation  ... 
arXiv:2102.03249v3 fatcat:vi2naw5spjhg7d2fuaec3b656y

Functional Modelling and Classification of Longitudinal Data*

HANS-GEORG MULLER
2005 Scandinavian Journal of Statistics  
This extension includes functional binary regression models for longitudinal data and is illustrated with data on primary biliary cirrhosis.  ...  We review and extend some statistical tools that have proved useful for analysing functional data.  ...  Acknowledgements This research was supported in part by NSF grants DMS02-04869 and DMS03-54448.  ... 
doi:10.1111/j.1467-9469.2005.00429.x fatcat:o3z5ttlsfjf5vkdhuhpdiizr2i

Copula Gaussian graphical models and their application to modeling functional disability data

Adrian Dobra, Alex Lenkoski
2011 Annals of Applied Statistics  
Our new models are called copula Gaussian graphical models (CGGMs) and embed graphical model selection inside a semiparametric Gaussian copula.  ...  We illustrate the use of the copula Gaussian graphical models in the analysis of a 16-dimensional functional disability contingency table.  ...  The authors are also grateful to Elena Erosheva who provided the NLTCS data. The authors thank the Editor and anonymous reviewers for their comments that improved the quality of this writing.  ... 
doi:10.1214/10-aoas397 fatcat:i3tass4fjnchvimwqqn66v42gy

Generative models for functional data using phase and amplitude separation

J. Derek Tucker, Wei Wu, Anuj Srivastava
2013 Computational Statistics & Data Analysis  
Ignoring phase variability leads to a loss of structure in the data and inefficiency in data models.  ...  In general, functional data contains both phase (or x or horizontal) and amplitude (or y or vertical) variability.  ...  Frank Crosby and Dr.  ... 
doi:10.1016/j.csda.2012.12.001 fatcat:3r24kohcybf7jilrl255fini2u

Joint models for grid point and response processes in longitudinal and functional data [article]

Daniel Gervini, Tyler J. Baur
2018 arXiv   pre-print
We apply the model to an online auction data set and show that there is a strong correlation between bidding patterns and price trajectories.  ...  The distribution of the grid points at which a response function is observed in longitudinal or functional data applications is often informative and not independent of the response process.  ...  We generated data from model (2)-(3)-(4) with p 1 = p 2 = 2.  ... 
arXiv:1705.06259v3 fatcat:uqwvqaqtdrdpbabmipacqjng5a

Function Modeling Improves the Efficiency of Spatial Modeling Using Big Data from Remote Sensing

2017 Big Data and Cognitive Computing  
procedures within a new GIS modeling framework called function modeling.  ...  Spatial models are typically composed of multiple sequential operations. Each operation reads data from a given data set, transforms the data, and then creates a new data set (Figure 1 ).  ...  Theoretically, processing time and storage space associated with creating raster data for a given model, computer configuration, set of operations, and data type should be a linear function of the total  ... 
doi:10.3390/bdcc1010003 fatcat:55egt3czvrgp3mqzqolujomoru

Smoothing and Mean–Covariance Estimation of Functional Data with a Bayesian Hierarchical Model

Jingjing Yang, Hongxiao Zhu, Taeryon Choi, Dennis D. Cox
2016 Bayesian Analysis  
Such a hierarchical framework is flexible enough to incorporate functional data with different characteristics, including data measured on either common or uncommon grids, and data with either stationary  ...  and an Inverse-Wishart process prior for the covariance function.  ...  Acknowledgments The authors would like to thank all colleagues in the PO1 project (supported by NIH grant PO1-CA-082710) for collecting the spectroscopy data and the Children's Nutrition Research  ... 
doi:10.1214/15-ba967 pmid:34457106 pmcid:PMC8387981 fatcat:pojdahmb2fbe3gyry65eojt4x4

Iterated function system models in data analysis: Detection and separation

Zachary Alexander, James D. Meiss, Elizabeth Bradley, Joshua Garland
2012 Chaos  
We investigate the use of iterated function system (IFS) models for data analysis.  ...  This method is tested on a simple IFS and applied to an experimental computer performance data set.  ...  Consequently, f 0 appears to be a continuous function and the IFS is an accurate model for this data set.  ... 
doi:10.1063/1.3701728 pmid:22757510 fatcat:4edegizbdnditcgtzvgy7ep2z4

Modeling and forecasting electricity spot prices: A functional data perspective

Dominik Liebl
2013 Annals of Applied Statistics  
The power of this new perspective is demonstrated by a forecast study that compares our functional factor model with two established classical time series models as well as two alternative functional data  ...  In a first step, the functional relation between electricity spot prices and electricity demand is modeled by daily price-demand functions.  ...  I want to thank Alois Kneip (University of Bonn) and Pascal Sarda (Université Paul Sabatier, Toulouse) for stimulating discussions. Section 6 profited especially from comments of the referees.  ... 
doi:10.1214/13-aoas652 fatcat:rayqayptajhptbxx2al6s3wuy4

Data Modelling and Conceptual Modelling: a comparative analysis of functionality and roles

T.William Olle
1993 Australasian Journal of Information Systems  
This paper reviews the functionality associated "data modelling" and "conceptual modelling".  ...  The requirements for a conceptual schema modelling facility over and above the functionality provided by currently available data modelling facilities are presented.  ...  There are several requirements for a conceptual schema modelling facility over and above the functionality provided by a typical data modelling facility and these are presented in detail in the following  ... 
doi:10.3127/ajis.v1i1.431 fatcat:yjje7iedfzfzrjrtrx2z7unwyq

Ising model for neural data: Model quality and approximate methods for extracting functional connectivity

Yasser Roudi, Joanna Tyrcha, John Hertz
2009 Physical Review E  
Finally, we study the quality of these models by comparing their entropies with that of the data.  ...  We study pairwise Ising models for describing the statistics of multi-neuron spike trains, using data from a simulated cortical network.  ...  of the entropy difference between the independent-neuron model and the data).  ... 
doi:10.1103/physreve.79.051915 pmid:19518488 fatcat:zxeowuat3fekpnzwbs4ky3tj54
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