Download or read book Efficient Estimation of Nested Logit Models written by David M. Brownstone and published by . This book was released on 1985 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book EFFICIENT ESTIMATION OF NESTED LOGIT MODELS AN APPLICATION TO TRIP TIMING NL written by Kenneth A. SMALL and published by . This book was released on 1982 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Efficient Estimation of nested logit models An application to trip timing written by Kenneth A. Small and published by . This book was released on 1982 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Efficient Estimation of Discrete choice Models from Choice based Samples written by Stephen Rhys Cosslett and published by . This book was released on 1979 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Discrete Choice Methods with Simulation written by Kenneth Train and published by Cambridge University Press. This book was released on 2009-07-06 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
Download or read book Logit Modeling written by Alfred DeMaris and published by SAGE. This book was released on 1992-06-06 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: Logit models : theoretical background. Logit models for multidimensional tables. Logistic regression. Advanced topics in logistic regression. Appendix : Computer routines.
Download or read book Determinants of Travel Choice written by David A. Hensher and published by . This book was released on 1978 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Comparison of Choice Models Representing Correlation and Random Taste Variation written by Laurie Anne Garrow and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A second theoretical contribution of this work relates to efficient estimation of nested logit models for choice-based samples. Currently, the benefit of collecting choice-based samples diminishes when modeling consumers' behavior using NL models because of the need to use consistent estimators that are often inefficient and/or complicated to implement. In contrast, benefits of using choice-based samples are retained when using the simple multinomial logit model because, under conditions that are relatively easy to satisfy in practice, the exogenous sample maximum likelihood estimator can be used. This study shows the exogenous sample maximum likelihood estimator can also be used with choice-based samples for NL models.
Download or read book Graph Theory with Applications written by C. Vasudev and published by New Age International. This book was released on 2006 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 1500 problems are used to illustrate concepts, related to different topics, and introduce applications.Over 1000 exercises in the text with many different types of questions posed. Precise mathematical language is used without excessive formalism and abstraction. Care has been taken to balance the mix of notation and words in mathematical statements. Problem sets are stated clearly and unambiguously, and all are carefully graded for various levels of difficulty. This text has been carefully designed for flexible use.
Download or read book Linear Probability Logit and Probit Models written by John H. Aldrich and published by SAGE. This book was released on 1984-11 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: After showing why ordinary regression analysis is not appropriate for investigating dichotomous or otherwise 'limited' dependent variables, this volume examines three techniques which are well suited for such data. It reviews the linear probability model and discusses alternative specifications of non-linear models.
Download or read book Improved Estimation of Flexible Logit Models and an Extension to a Model with a T distributed Error Kernel written by Prateek Bansal and published by . This book was released on 2019 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding various micro-decisions of travelers (e.g., choice of vehicles, travel modes, or destinations) is of utmost importance in travel demand modeling. After the first application of the multinomial logit model in the early 1970s, micro-econometric models to elicit these type of choices have evolved in mainly two ways: a) computationally efficient estimation (e.g., fast integral approximations); and b) behaviorally defensible models (e.g., modeling preference heterogeneity). This dissertation contributes to both lines of behavior modeling research -- whereas chapters one to three analyze and improve the computational efficiency of flexible logit models and the required approximation of high-dimensional integrals, chapter four derives the first multinomial response model with a t-distributed error kernel that accounts for decision uncertainty behavior of travelers. A summary of each chapter is provided below. In Chapter 1, we extend the logit-mixed logit (LML) model, an advanced semi-parametric specification of preference heterogeneity, to a combination of fixed and random parameters. We show that the likelihood of the LML specification loses its special properties due to the inclusion of fixed parameters, leading to a much higher estimation time. In an empirical application about preferences for alternative fuel vehicles in China, estimation time increased by a factor of 20-40 when introducing fixed parameters. Despite losses in computation efficiency, we show that the flexible LML could retrieve multimodal mixing distributions. In Chapter 2, we derive, implement, and test minorization-maximization (MM) algorithms to estimate the semiparametric LML and mixture-of-normals multinomial logit (MON-MNL) models. In a Monte Carlo study and empirical application to estimate consumer's willingness to adopt electric motorcycles in Indonesia, we compare the maximum simulated likelihood estimator (MSLE) with the derived MM algorithms. Whereas in LML estimation MM is computationally noncompetitive with MSLE, it is a competitive replacement to MSLE for MON-MNL that obviates computation of complex analytical gradients. In Chapter 3, we propose the application of a moment-based designed quadrature (DQ) method to approximate multi-dimensional integrals in MSLE of discrete choice models. The results of simulation study indicate that DQ is a potentially attractive alternative to quasi-Monte Carlo (QMC) because it requires fewer evaluations of the conditional likelihood (i.e., lower computation time) as compared to QMC methods, is as easy to implement, ensures positivity of weights, and can be created on any general polynomial spaces. Finally, we validate the performance of DQ on a case study to understand preferences for mobility-on-demand services in New York City. In Chapter 4, we demonstrate that using a t-distributed error kernel in multinomial choice models helps in better predicting the preferences in class-imbalance datasets. This specification also implicitly accounts for the consumers' decision uncertainty behavior. Because of these statistical and behavioral advantages, we derive the first multinomial response model with a t-distributed error kernel and extend this to a generalized continuous-multinomial (GCM) model. In the empirical stu.
Download or read book Stated Choice Methods written by Jordan J. Louviere and published by Cambridge University Press. This book was released on 2000-09-28 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: A multidisciplinary graduate and practitioner guide, first published in 2000, which offers the theory and application of stated choice methods.
Download or read book Logit Modeling written by Alfred DeMaris and published by . This book was released on 1992 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'Logit Modeling' represents a breakthrough for researchers because it offers ways for more efficient estimation of models with multiple categorical variables, particularly whenever the measurement assumptions for classical multiple regression fail to be met.
Download or read book Logit Models from Economics and Other Fields written by J. S. Cramer and published by Cambridge University Press. This book was released on 2003-08-21 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Logistic models are widely used in economics and other disciplines and are easily available as part of many statistical software packages. This text for graduates, practitioners and researchers in economics, medicine and statistics, which was originally published in 2003, explains the theory underlying logit analysis and gives a thorough explanation of the technique of estimation. The author has provided many empirical applications as illustrations and worked examples. A large data set - drawn from Dutch car ownership statistics - is provided online for readers to practise the techniques they have learned. Several varieties of logit model have been developed independently in various branches of biology, medicine and other disciplines. This book takes its inspiration from logit analysis as it is practised in economics, but it also pays due attention to developments in these other fields.
Download or read book Handbook on Entropy Complexity and Spatial Dynamics written by Reggiani, Aura and published by Edward Elgar Publishing. This book was released on 2021-12-14 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: This ground-breaking Handbook presents a state-of-the-art exploration of entropy, complexity and spatial dynamics from fundamental theoretical, empirical and methodological perspectives. It considers how foundational theories can contribute to new advances, including novel modeling and empirical insights at different sectoral, spatial and temporal scales.
Download or read book Advanced Econometrics written by Takeshi Amemiya and published by Harvard University Press. This book was released on 1985 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main features of this text are a thorough treatment of cross-section models—including qualitative response models, censored and truncated regression models, and Markov and duration models—and a rigorous presentation of large sample theory, classical least-squares and generalized least-squares theory, and nonlinear simultaneous equation models.
Download or read book Logit and Probit written by Vani K. Borooah and published by SAGE. This book was released on 2002 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many problems in the social sciences are amenable to analysis using the analytical tools of logit and probit models. This book explains what ordered and multinomial models are and also shows how to apply them to analysing issues in the social sciences.
