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Exact Logit-Based Product Design [article]

İrem Akçakuş, Velibor V. Mišić
2021 arXiv   pre-print
At the heart of our methodology is the surprising result that the logit-based SOCPD problem can be exactly reformulated as a mixed-integer convex program.  ...  In this paper, we develop an exact methodology for solving this problem based on modern integer, convex and conic optimization.  ...  Acknowledgments The authors thank the authors of Toubia et al. (2003) , Hainmueller et al. (2014) and Allenby and Ginter (1995) for making their data sets available, which were used in the experiments  ... 
arXiv:2106.15084v1 fatcat:4ud527p7jjhyfb5dcenqsiq3c4

Optimizing Offer Sets in Sub-Linear Time [article]

Vivek F. Farias, Andrew A. Li, Deeksha Sinha
2020 arXiv   pre-print
Our algorithm works for an extremely general class of problems and models of user choice that includes the mixed multinomial logit model as a special case.  ...  Thus motivated, we propose an algorithm for personalized offer set optimization that runs in time sub-linear in the number of items while enjoying a uniform performance guarantee.  ...  For example, taking the 's to be Gumbel random variables yields the multinomial logit model, and allowing for random U yields the mixed multinomial logit.  ... 
arXiv:2011.08606v1 fatcat:4lorwousdfdozl4cyq5w7x3erq

Frequentist model averaging for multinomial and ordered logit models

Alan T.K. Wan, Xinyu Zhang, Shouyang Wang
2014 International Journal of Forecasting  
a r t i c l e i n f o Keywords: Asymptotic squared error risk Local mis-specification Model screening Monte Carlo Plug-in estimator a b s t r a c t Multinomial and ordered Logit models are quantitative  ...  Our strategy of weight choice for the candidate models is based on the minimization of a plug-in estimator of the asymptotic squared error risk of the model average estimator.  ...  Acknowledgments The authors thank the editor Graham Elliot, the associate editor and two referees for very helpful comments and suggestions.  ... 
doi:10.1016/j.ijforecast.2013.07.013 fatcat:wionh2mopzgwxjsqnuv763q7ri

Regularized Ordinal Regression and the ordinalNet R Package

Michael J. Wurm, Paul J. Rathouz, Bret M. Hanlon
2021 Journal of Statistical Software  
Finally, we introduce the R package ordinalNet, which implements the algorithm for this model class.  ...  perform variable selection.  ...  Acknowledgments The authors thank Alex Tahk for the suggestion that led them to explore shrinking the nonparallel model to the parallel model.  ... 
doi:10.18637/jss.v099.i06 pmid:34512213 pmcid:PMC8432594 fatcat:go5si5pturbolgde6utshw6sem

A Generalized Markov Chain Model to Capture Dynamic Preferences and Choice Overload [article]

Kumar Goutam, Vineet Goyal, Agathe Soret
2020 arXiv   pre-print
Assortment optimization is an important problem that arises in many industries such as retailing and online advertising where the goal is to find a subset of products from a universe of substitutable products  ...  While we show that the assortment optimization under this model is NP-hard, we present fully polynomial-time approximation scheme (FPTAS) under reasonable assumptions.  ...  For example, one could potentially estimate a different logit or mixed logit model for each assortment offered to consumers, which would allow the preference parameters to vary with assortment.  ... 
arXiv:1911.06716v4 fatcat:wijawsx5iramnbtfj7wknelnam

Regularized Ordinal Regression and the ordinalNet R Package [article]

Michael J. Wurm, Paul J. Rathouz, Bret M. Hanlon
2017 arXiv   pre-print
Finally, we introduce the R package ordinalNet, which implements the algorithm for this model class.  ...  perform variable selection.  ...  Acknowledgements The authors thank Alex Tahk for the suggestion that led them to explore shrinking the nonparallel model to the parallel model.  ... 
arXiv:1706.05003v1 fatcat:mibuxhr22vfbdhxgrldwpz5a4y

Feature selection for high-dimensional temporal data

Michail Tsagris, Vincenzo Lagani, Ioannis Tsamardinos
2018 BMC Bioinformatics  
Feature selection is commonly employed for identifying collectively-predictive biomarkers and biosignatures; it facilitates the construction of small statistical models that are easier to verify, visualize  ...  Conclusions: The use of this algorithm is suggested for variable selection with high-dimensional temporal data.  ...  Acknowledgements The first author would like to express his acknowledgments to Dimitris Rizopoulos and Janice Scealy for answering some of his questions.  ... 
doi:10.1186/s12859-018-2023-7 pmid:29357817 pmcid:PMC5778658 fatcat:6jjgibl3rfbp5n3kfgn4svpvli

JointAI: Joint Analysis and Imputation of Incomplete Data in R [article]

Nicole S. Erler, Dimitris Rizopoulos, Emmanuel M. E. H. Lesaffre
2020 arXiv   pre-print
JointAI provides functions for Bayesian inference with generalized linear and generalized linear mixed models and extensions thereof as well as survival models and joint models for longitudinal and survival  ...  Usage and features of JointAI are described and illustrated using various examples and the theoretical background is outlined.  ...  Multinomial logit (mixed) models Multinomial logit mixed models are implemented as y ij ∼ Mult(π ij,1 , . . . , π ij,K ), π ij,k = φ i,k / K q=1 φ i,q , k ∈ 1, . . . , K, log(φ ij,1 ) = 0, log(φ ij,k )  ... 
arXiv:1907.10867v3 fatcat:x2fw7p6usva6fn7le6eanmzp2y

Multivariate Fractional Regression Estimation of Econometric Share Models

John Mullahy
2015 Journal of Econometric Methods  
AbstractThis paper describes and applies econometric strategies for estimating regression models of economic share data outcomes where the shares may take boundary values (zero and 1) with nontrivial probability  ...  "Econometric Methods for Fractional Response Variables with an Application to 401(k) Plan Participation Rates."  ...  In addition, Badi Baltagi and Jeff Wooldridge provided some helpful guidance with the literature. All these colleagues, of course, are absolved from any blame for the paper's shortcomings.  ... 
doi:10.1515/jem-2012-0006 pmid:30079291 pmcid:PMC6075740 fatcat:rrorkq5hjzaz3njjp5jptt7ciu

Pricing structure optimization in mixed restricted/unrestricted fare environments

Joern Meissner, Arne K Strauss
2010 Journal of Revenue and Pricing Management  
To that end, we formulate the problem as a dynamic program and approximate it with a mixed integer linear program (MIP) that selects the best price points out of a potentially large set of price candidates  ...  We develop choice-based network revenue management approaches for such a mixed fare environment that can handle both the traditional opening or closing of restricted fare classes as well as handling pricing  ...  A choice model suited to this task is the Multinomial Logit (MNL) with overlapping consideration sets, see Miranda Bront et al. (2009) , for example.  ... 
doi:10.1057/rpm.2010.33 fatcat:xnmjnruyirev5a4ai5hcq3dp6y

Multi-agent Assortment Optimization in Sequential Matching Markets [article]

Alfredo Torrico, Margarida Carvalho, Andrea Lodi
2021 arXiv   pre-print
Suppliers observe the subset of consumers that selected them, and choose either to match a consumer or leave the system.  ...  Given the computational complexity of the problem, we show several constant factor guarantees for the general model that, in particular, significantly improve the approximation factors previously obtained  ...  Acknowledgements The second author thanks the support of the Institut de valorisation des données (IVADO) and Fonds de recherche du Québec (FRQ) through the FRQ-IVADO Research Chair and of the Natural  ... 
arXiv:2006.04313v2 fatcat:bbkz3o3jvnet3cfado5onfdtui

Choice Set Optimization Under Discrete Choice Models of Group Decisions [article]

Kiran Tomlinson, Austin R. Benson
2020 arXiv   pre-print
Here, we use discrete choice modeling to develop an optimization framework of such interventions for several problems of group influence, namely maximizing agreement or disagreement and promoting a particular  ...  We design approximation algorithms for the hard problems and show that they work well on real-world choice data.  ...  We thank Johan Ugander for helpful conversations.  ... 
arXiv:2002.00421v2 fatcat:lq3rcr67vjf6bcbtqkvzg5gxrq

Activity-based Market Equilibrium for Capacitated Multimodal Transport Systems

Joseph Y.J. Chow, Shadi Djavadian
2015 Transportation Research Procedia  
The model is based on a constrained mixed logit model of activity schedule choice, where each schedule in the choice set is generated with a multimodal extension of the Household Activity Pattern Problem  ...  The market equilibrium is achieved with Lagrangian relaxation to determine the optimal dual price of the capacity constraint, and a method of successive averages with column generation finds an efficient  ...  The authors wish to thank the University of Toronto's Data Management Group for the Transportation Tomorrow Survey data used in this study, and to Susan Jia Xu for her help preparing some initial data  ... 
doi:10.1016/j.trpro.2015.06.001 fatcat:vthj6xlry5bubi34sir75rspd4

Data‐driven research in retail operations—A review

Meng Qi, Ho‐Yin Mak, Zuo‐Jun Max Shen
2020 Naval Research Logistics  
We then conclude the paper by pointing out some interesting future research possibilities for our community.  ...  We survey state-of-the-art studies in three core aspects of retail operations-assortment optimization, order fulfillment, and inventory management.  ...  ACKNOWLEDGMENTS The authors gratefully acknowledge feedback from Professor Ming Hu (Editor-in-Chief), the Associate Editor, and two anonymous referees, which have helped improve this article.  ... 
doi:10.1002/nav.21949 fatcat:lktqqpvc3fhebglrmtb3xjp7mq

Bayesian inference for categorical data analysis

Alan Agresti, David B. Hitchcock
2005 Statistical Methods & Applications  
Adopted usually in a hierarchical form, the logit-normal approach allows greater flexibility and scope for generalization. The 1970s also saw considerable interest in loglinear modeling.  ...  The advent of modern computational methods since the mid-1980s has led to a growing literature on fully Bayesian analyses with models for categorical data, with main emphasis on generalized linear models  ...  The authors thank Jon Forster for many helpful comments and suggestions about an earlier draft and thank him and Steve Fienberg and George Casella for suggesting relevant references.  ... 
doi:10.1007/s10260-005-0121-y fatcat:3ya3smjjzfagxgx6q6bicp43rq
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