Mixed Logit with Bounded Distributions of Correlated Partworths

By Kenneth Train, Garrett P. Sonnier. 2005

347 citations recorded by the source corpus.

Subfields: Applied Mathematics, Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/fa507ca27e7f0795a966212541a3bdd342c638d2

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Citations in the corpus

Augmenting short Cheap Talk scripts with a repeated Opt-Out Reminder in Choice Experiment surveys (2014, background): “Secondly, and more importantly, it avoids a number of severe problems associated with specifying a random price parameter (for further details, the reader is referred to e.g. Meijer and Rouwendal 2006; Hensher et al. 2005; Hess et al. 2005; Train and Sonnier 2005; Campbell et al. 2006; Hensher and G”
Visual Attention and Attribute Attendance in Multi-Attribute Choice Experiments (2015, methodology): “The conditional posterior distributions for the first three components (i.e., i, ii, iii) are the same as in Train and Sonnier (2005).”
Handling respondent uncertainty in Choice Experiments: Evaluating recoding approaches against explicit modelling of uncertainty (2009, background): “The true distribution is unknown, so in principle any distribution could be applied (Carlsson et al., 2003; Hensher and Greene, 2003), and the normal is the most easily applied (Train and Sonnier, 2005).”
Route choice modeling: past, present and future research directions (2009, background): “Different discrete choice applications introduce bounded distributions for coefficients of variables with an expected sign (see, e.g., Train and Sonnier, 2005; Hess et al., 2005), but literature in the route choice context does not report the investigation of these distributions.”
Valuing externalities from water supply: Status quo, choice complexity and individual random effects in panel kernel logit analysis of choice experiments (2007, background): “The latter is often a difficult interpretation when the choice of distribution spans the entire support of the real line (for discussion of alternatives see, for example, Hensher & Greene, 2003; Train & Sonnier, 2005).”
Modeling Elicitation effects in contingent valuation studies: a Monte Carlo Analysis of the bivariate approach (2005, methodology): “The use of bounded distributions is in this case preferable ( Train and Sonnier, 2005, Hess, Bierlaire and Polak, 2004).”
Farmers' willingness to provide ecosystem services and effects of their spatial distribution (2013, background): “This however avoids a number of potentially severe problems associated with specifying a random price parameter for the following calculation of WTA (see e.g. Hensher et al., 2005; Train and Sonnier, 2005).”
Effects on Welfare Measures of Alternative Means of Accounting for Preference Heterogeneity in Recreational Demand Models (2008, neutral): “…are stronger when using maximum simulated likelihood because of its reliance on gradient methods to find the maximum (Rigby and Burton 2005; Train and Sonnier 2005), but more choice exists when using hierarchical Bayes estimation (Sillano and Ortuzar 2005) in which convergence is…”
Applying discrete choice models to predict Academy Award winners (2008, methodology): “The analogous quantity for the same model fitted by using WinBUGS is also 0.47 (as noted in Section 3, to ease comparison of our maximum likelihood and Bayesian approaches we follow Train and Sonnier (2005) by evaluating Bayesian results by using both Bayesian and classical procedures).”
Choosing Between Internet and Mail Survey Modes for Choice Experiment Surveys Considering Non-Market Goods (2009, background): “Second, and more importantly, it avoids a number of severe problems associated with specifying a random price parameter (see Meijer and Rouwendal 2006; Hensher et al. 2005; Hess et al. 2005; Train and Sonnier 2005; Campbell et al. 2006; Hensher and Greene 2003; Rigby and Burton 2006; Train 2003; Tra”
On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice (2006, methodology): “For a discussion of the risks involved, and on guidance for which approach should be used, see for example Train and Sonnier (2003), Hensher and Greene (2001), Hess and Polak (2004) and Hess et al. (2004) .”
EM algorithms for nonparametric estimation of mixing distributions (2008, methodology): “In the application by Train and Sonnier (2005), for example, lognormals and truncated normals gave a considerably higher LL than normals.”
Benefit Estimates for Landscape Improvements: Sequential Bayesian Design and Respondents’ Rationality in a Choice Experiment (2005, background): “variation in random utility models see Train and Sonnier (2005) who propose a Bayesian estimation approach, for an application of bounding directly to the expenditure function see Train and Weeks (2005).”
Foundations of Stated Preference Elicitation: Consumer Behavior and Choice-based Conjoint Analysis (2019, methodology): “…models, using MSL rather than MSS, are Ben-Akiva et al. (1993), Revelt and Train (1998), Train (1998,1999, 2007, 2009), Brownstone and Train (1999), Brownstone, Bunch, and Train (2000), Chesher and Santos-Silva (2002), Hensher and Green (2002), Train and Sonnier (2005), and Walker et al. (2007).”