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Automatically identifying scatter in fluorescence data using robust techniques

Sanne Engelen, Stina Frosch Møller, Mia Hubert
2007 Chemometrics and Intelligent Laboratory Systems  
First and second order Rayleigh and Raman scatter is a common problem when fitting Parallel Factor Analysis (PARAFAC) to fluorescence excitation-emission data (EEM).  ...  The scatter does not contain any relevant chemical information and does not conform to the low-rank trilinear model. The scatter complicates the analysis instead and contributes to model inadequacy.  ...  The three loadings with a narrow, but high peak, are fitting the scattering instead of chemically relevant information.  ... 
doi:10.1016/j.chemolab.2006.08.001 fatcat:hczgukevdfac7isyeo2k7wlik4

Simultaneous localization and separation of biomedical signals by tensor factorization

Bahador Makki Abadi, Delaram Jarchi, Saeid Sanei
2009 2009 IEEE/SP 15th Workshop on Statistical Signal Processing  
We represent multi-channel EEG data using a third-order tensor with modes: space (channels), time samples and number of segments.  ...  In this paper, we introduce mathematical models based on multi-way data construction and analysis with a goal of simultaneously separating and localizing the sources in the brain by analysis of scalp electroencephalogram  ...  Directly fitting PARAFAC2 on raw data has more advantages than indirect fitting in terms of imposing constraints, handling missing data and generalization of the model to N-way arrays [5] .  ... 
doi:10.1109/ssp.2009.5278529 fatcat:6m3vwt65hbekdamk6rgcng5xsi

Unsupervised Multiway Data Analysis: A Literature Survey

E. Acar, B. Yener
2009 IEEE Transactions on Knowledge and Data Engineering  
Standard two-way methods commonly applied on matrices often fail to find the underlying structures in multiway arrays.  ...  Multiway data analysis captures multilinear structures in higher-order datasets, where data have more than two modes.  ...  In particular, we would like to thank Rasmus Bro and Tamara G. Kolda for their contributions to this survey through their comments and invaluable guidance in multiway data analysis.  ... 
doi:10.1109/tkde.2008.112 fatcat:v2wevzw53zaotja3wrllxff3qa

Comparison of Methods for Handling Missing Covariate Data

Åsa M. Johansson, Mats O. Karlsson
2013 AAPS Journal  
Missing covariate data is a common problem in nonlinear mixed effects modelling of clinical data.  ...  Three different types of missing data mechanisms were simulated and information about sex was missing for 50% of the individuals.  ...  ACKNOWLEDGEMENTS The research leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115156, resources of which are composed  ... 
doi:10.1208/s12248-013-9526-y pmid:24022319 pmcid:PMC3787222 fatcat:f4m5aiuikjh5hjrzksw7olkdxq

Three-way cluster and component analysis of maize variety trials

P. M. Kroonenberg, K. E. Basford, A. G. M. Ebskamp
1995 Euphytica  
Data from the Dutch Variety List Trials for maize were analysed with three-way mixture method clustering and three-mode component analysis.  ...  The main objective of the paper is to demonstrate the usefulness of such multivariate analysis techniques for plant breeding data.  ...  The methods to be presented in this paper are the three-way mixture method of clustering, as fully described in Basford & McLachlan (1985) , McLachlan & Basford (1988) and three-way (or three-mode)  ... 
doi:10.1007/bf01677554 fatcat:hod5au4pijh6jprqxrlhi6qbey

Fitting Finite Mixtures of Generalized Linear Regressions on Motor Insurance Claims

Nana Kena Frempong
2017 International Journal of Statistical Distributions and Applications  
These mixture models were fitted to the claims data and measures of goodness-of-fit (AIC and BIC) were used to determine the best mixture model.  ...  This in a way may inform decision makers as to the kind of anticipated reserves for future claims.  ...  The model with the least values of AIC and BIC indicates the best fitted model to the claims data.  ... 
doi:10.11648/j.ijsd.20170304.19 fatcat:mmnoygqjdvfkpce63q4syv5eoa

Structure preserving feature selection in PARAFAC using a genetic algorithm and Procrustes analysis

W Wu, Q Guo, D.L Massart, C Boucon, S de Jong
2003 Chemometrics and Intelligent Laboratory Systems  
The method was applied to two industrial data sets: a three-way sensory data set and a four-way gas chromatography (GC) data set.  ...  In this paper, a method is proposed to select subsets of variables in parallel factor analysis (PARAFAC), such that information in the complete multi-way data set is preserved as much as possible.  ...  Acknowledgements The authors thank the EU for the financial assistance on the N-way methods project.  ... 
doi:10.1016/s0169-7439(02)00105-3 fatcat:l5agc5c5wnbrrhjwmesu6axk6u

Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations

Jukka Corander, Pekka Marttinen, Jukka Sirén, Jing Tang
2008 BMC Bioinformatics  
With these methods it is possible, e.g., to fit genetic mixture models using user-specified numbers of clusters and to estimate levels of admixture under a genetic linkage model.  ...  We discuss the necessity of enhancing the statistical approaches to face the challenges posed by the ever-increasing amounts of molecular data generated by scientists over a wide range of research areas  ...  by not fitting models with three or more clusters.  ... 
doi:10.1186/1471-2105-9-539 pmid:19087322 pmcid:PMC2629778 fatcat:7s5crgixjnedth7w3w5vyq66t4

Termination of a visual search with large display size effects

Denis Cousineau, Richard Shiffrin
2004 Spatial Vision  
The ability to locate an object in the visual field is a collaboration of at least three intermingled processes: scanning multiple locations, recognizing the object sought (the target), and ending the  ...  We present models to account for these findings. The distributions of terminations help determine the slopes of the functions relating response time to set size.  ...  Acknowledgements We would like to thank Lori Arnold, Judy Blackburn, Amy Criss, Alicia Justus and Peter Murray for their comments on an earlier version of this text.  ... 
doi:10.1163/1568568041920104 pmid:15559108 fatcat:5rapxg42infrndhjf2putcnf4u

components?an alternative to reversible jump methods

Matthew Stephens
2000 Annals of Statistics  
Richardson and Green present a method of performing a Bayesian analysis of data from a finite mixture distribution with an unknown number of components.  ...  We describe an alternative MCMC method which views the parameters of the model as a (marked) point process, extending methods suggested by Ripley to create a Markov birth-death process with an appropriate  ...  I would like to thank my D.Phil. supervisor, Professor Brian Ripley, for suggesting this approach to the problem, and for valuable comments on earlier versions.  ... 
doi:10.1214/aos/1016120364 fatcat:nag2zue6zneilkkiy4f3bvnkiu

Multi-Way Analysis Coupled with Near-Infrared Spectroscopy in Food Industry: Models and Applications

Huiwen Yu, Lili Guo, Mourad Kharbach, Wenjie Han
2021 Foods  
The combination of a multi-way analysis with NIRS will be a promising practice for turning food data information into operational knowledge, conducting reliable food analyses and improving our understanding  ...  To the best of our knowledge, this is the first paper that systematically reports the advances on models and applications of a multi-way analysis in NIRS for the food industry.  ...  Acknowledgments: We would like to acknowledge our appreciation to Rasmus Bro and Frans W.J. van den Berg of our chemometrics group in University of Copenhagen for their helpful comments in the course of  ... 
doi:10.3390/foods10040802 pmid:33917964 pmcid:PMC8068357 fatcat:wvuckuo57jbvvhketkdv7gul2y

How to Select the Best Fit Model among Bayesian Latent Growth Models for Complex Data

Laura Lu, Zhiyong Zhang
2022 Journal of Behavioral Data Science  
mixture models with missing data and outliers, extended growth mixture models with missing data and outliers, and latent growth models with different classes.  ...  The goal of this study is to propose new model selection indices and to investigate their performances in the framework of latent growth mixture models with missing data and outliers in a Bayesian context  ...  Acknowledgment The study was supported by a grant from the Institute of Education Sciences (R305D210023).  ... 
doi:10.35566/jbds/v2n1/p2 fatcat:e7dgbxvwxbgzrog6qjyplgdonq

Automated Feature Extraction in Brain Tumor by Magnetic Resonance Imaging Using Gaussian Mixture Models

Ahmad Chaddad
2015 International Journal of Biomedical Imaging  
In FLAIR mode the accuracy decreased to 94.11% (AUC = 95.85%) with 0.00% missed detection and 5.89% false alarm.  ...  This paper presents a novel method for Glioblastoma (GBM) feature extraction based on Gaussian mixture model (GMM) features using MRI.  ...  Table 1 shows a comparative study between the three modes of MR images based on the classifier accuracy, false alarm, and missed detection.  ... 
doi:10.1155/2015/868031 pmid:26136774 pmcid:PMC4469084 fatcat:4yo5kwuzjzganhomyfvj3r3e7m

A weakly informative default prior distribution for logistic and other regression models

Andrew Gelman, Aleks Jakulin, Maria Grazia Pittau, Yu-Sung Su
2008 Annals of Applied Statistics  
We implement a procedure to fit generalized linear models in R with the Student-t prior distribution by incorporating an approximate EM algorithm into the usual iteratively weighted least squares.  ...  We illustrate with several applications, including a series of logistic regressions predicting voting preferences, a small bioassay experiment, and an imputation model for a public health data set.  ...  The direct approach to imputing missing data in several variables is to fit a multivariate model.  ... 
doi:10.1214/08-aoas191 fatcat:ox22ethoond7ffkgrkes2rcipq

ATSAS2.1, a program package for small-angle scattering data analysis

Petr V. Konarev, Maxim V. Petoukhov, Vladimir V. Volkov, Dmitri I. Svergun
2006 Journal of Applied Crystallography  
The programs included in the package cover the major processing and interpretation steps from primary data reduction to three-dimensional modelling.  ...  The program packageATSAS2.1 for small-angle X-ray and neutron scattering data analysis is presented.  ...  Kuprin for the experimental data from tricorn protease and reverse transcriptase, respectively.  ... 
doi:10.1107/s0021889806004699 fatcat:r53mxttnyjegpaf64v6niqlkr4
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