Journal articles: 'Multiple discrete-continuous choices'

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Tapia, Rodrigo J., Gerard de Jong, Ana M. Larranaga, and Helena B. Bettella Cybis. "Exploring Multiple‐discreteness in Freight Transport. A Multiple Discrete Extreme Value Model Application for Grain Consolidators in Argentina." Networks and Spatial Economics 21, no. 3 (May 25, 2021): 581–608. http://dx.doi.org/10.1007/s11067-021-09531-y.

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AbstractThere are some examples where freight choices may be of a multiple discrete nature, especially the ones at more tactical levels of planning. Nevertheless, this has not been investigated in the literature, although several discrete-continuous models for mode/vehicle type and shipment size choice have been developed in freight transport. In this work, we propose that the decision of port and mode of the grain consolidators in Argentina is of a discrete-continuous nature, where they can choose more than one alternative and how much of their production to send by each mode. The Multiple Discrete Extreme Value Model (MDCEV) framework was applied to a stated preference data set with a response variable that allowed this multiple-discreteness. To our knowledge, this is the only application of the MDCEV in regional freight context. Free alongside ship price, freight transport cost, lead-time and travel time were included in the utility function and observed and random heterogeneity was captured by the interaction with the consolidator’s characteristics and random coefficients. In addition, different discrete choice models were used to compare the forecasting performance, willingness to pay measures and structure of the utility function against.

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Vallejo-Borda, Jose Agustin, Eeshan Bhaduri, Hernan Alberto Ortiz-Ramirez, Julián Arellana, Charisma F. Choudhury, Alvaro Rodriguez-Valencia, Zia Wadud, and Arkopal K. Goswami. "Modeling the COVID-19 Travel Choices in Colombia and India: A Hybrid Multiple Discrete-Continuous Nested Extreme Value Approach." Transportation Research Record: Journal of the Transportation Research Board 2677, no. 4 (April 2023): 778–801. http://dx.doi.org/10.1177/03611981231162588.

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The COVID-19 pandemic has affected many daily activities, primarily as a result of the perceived contagion risk and government restrictions to mitigate the spread of the virus. To this end, drastic changes in the trip choices for commuting to work have been reported and studied, mostly through descriptive analysis. On the other hand, modeling-based research that can simultaneously understand both changes in mode choice and its frequency at an individual level has not been much used in existing studies. As such, this study aims to understand the changes in mode-choice preference and the frequency of trips, comparing pre-COVID with during-COVID scenarios, in two different countries of the Global South: Colombia and India. A hybrid multiple discrete-continuous nested extreme value model was implemented using the data obtained from online surveys in Colombia and India during the early COVID-19 period of March and April 2020. This study found that, in both countries, utility related to active modes (more used) and public transportation (less used) changed during the pandemic. In addition, this study highlights potential risks in likely unsustainable futures where there may be increased use of private vehicles such as cars and motorcycles, in both countries. It was also identified that perceptions toward government responses had a significant impact on the choices in Colombia, though this was not the case in India. These results may help decision makers focus on public policies to encourage sustainable transportation by avoiding the detrimental long-term behavioral changes resulting from the COVID-19 pandemic.

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Varghese, Varun, Makoto Chikaraishi, and Hironori Kato. "Analysis of Travel-Time Use in Crowded Trains using Discrete-Continuous Choices of Commuters in Tokyo, Japan." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 10 (July 22, 2020): 189–98. http://dx.doi.org/10.1177/0361198120934794.

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Travel-based multitasking and the possibility to perform activities during travel are important factors that can make a transportation mode attractive. However, serious crowding in public transportation systems might adversely affect the passengers’ free choice to participate in activities during travel. This study aims to examine how crowding in public transportation systems is related to discrete-continuous choices in different types of multitasking options using a data set of 500 commuters in the Tokyo Metropolitan Area. Employing a multiple discrete-continuous extreme value model, this study investigates the relationship between crowding levels and multitasking behavior. The results show that high crowding levels, relative to being seated, have a significantly negative association with many multitasking options, which suggests the importance of seat availability. The estimation results also show that information and communication technology (ICT)-dependent leisure activities and non-ICT active activities, such as reading and talking with other passengers, have the lowest satiation and higher baseline preference constants, which indicates that they are preferred by passengers. Meanwhile, crowding levels were observed to have a significant relationship with these multitasking activities. Finally, the key findings, contributions, and policy implications of the findings are discussed.

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Paleti, Rajesh, and Ivana Vukovic. "Telecommuting and Its Impact on Activity–Time Use Patterns of Dual-Earner Households." Transportation Research Record: Journal of the Transportation Research Board 2658, no. 1 (January 2017): 17–25. http://dx.doi.org/10.3141/2658-03.

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Telecommuting choices of workers in multiworker households are likely to be interdependent. These telecommuting choices may also affect the activity–time use choices of all people in the household. From the standpoint of travel behavior and travel demand forecasting, it is important to test these hypotheses and quantify the relationship between telecommuting choices and activity–time use patterns. To do this, the present study developed a generalized extreme value–based joint count model for analyzing the monthly frequency of choosing to telecommute of workers in dual-earner households. A panel multiple discrete continuous extreme value model was also developed to study activity–time use decisions while accounting for household-level interaction effects. The study findings confirm the presence of strong intrahousehold interaction effects in both the telecommuting and activity–time use choices of workers. Telecommuting choices were found to have a significant influence on daily activity–time use decisions for both mandatory and nonmandatory activities.

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Park, Yun-Sun, and Jae Bong Chang. "Measuring Beef Demand by Country of Origin and Cooking Purpose: The Multiple Discrete-Continuous Extreme Value Model Approach." Korean Agricultural Economics Association 64, no. 2 (June 30, 2023): 1–19. http://dx.doi.org/10.24997/kjae.2023.64.2.1.

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There has been a steady increase in the consumption of Korean beef in recent years, with the per capita consumption of beef reaching a record high in 2022. The domestic beef market provides consumers with more choices, so traditional methods of demand analysis that rely on whole beef products are likely to become less useful. Employing the multiple discrete-continuous extreme value model (MDCEV), we analyze scanner data on consumer panels over a long period. Our findings indicate Hanwoo beef demand is less price sensitive than other beef types. Furthermore, Hanwoo beef has a relatively larger cross-price elasticity than other alternatives. Consumers' income, age, and household size also significantly affect the interrelationship between demand and supply. Higher-income consumers are more likely to choose Hanwoo beef and less likely to choose imported beef. Larger families are more likely to select beef for grilling rather than cooking. These results explain current beef expenditure patterns and help understand how consumers make decisions.

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Enam, Annesha, Karthik C. Konduri, Abdul R. Pinjari, and Naveen Eluru. "An integrated choice and latent variable model for multiple discrete continuous choice kernels: Application exploring the association between day level moods and discretionary activity engagement choices." Journal of Choice Modelling 26 (March 2018): 80–100. http://dx.doi.org/10.1016/j.jocm.2017.07.003.

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Wang, Yanwen, Michael Lewis, and Vishal Singh. "Investigating the Effects of Excise Taxes, Public Usage Restrictions, and Antismoking Ads Across Cigarette Brands." Journal of Marketing 85, no. 3 (April 14, 2021): 150–67. http://dx.doi.org/10.1177/0022242921994566.

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The prevalence of strong brands such as Coca-Cola, McDonald’s, Budweiser, and Marlboro in “vice” categories has important implications for regulators and consumers. While researchers in multiple disciplines have studied the effectiveness of antitobacco countermarketing strategies, little attention has been given to how brand strength may moderate the efficacy of tactics such as excise taxes, usage restrictions, and educational advertising campaigns. In this research, the authors use a multiple discrete-continuous model to study the impact of antismoking techniques on smokers’ choices of brands and quantities. The results suggest that although cigarette excise taxes decrease smoking rates, these taxes also result in a shift in market share toward stronger brands. Market leaders may be less affected by tax policies because their market power allows strong brands such as Marlboro to absorb rather than pass through increased taxes. In contrast, smoke-free restrictions cause a shift away from stronger brands. In terms of antismoking advertising, the authors find minimal effects on brand choice and consumption. The findings highlight the importance of considering brand asymmetries when designing a policy portfolio on cigarette tax hikes, smoke-free restrictions, and antismoking advertising campaigns.

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Berke, Joshua D., Jason T. Breck, and Howard Eichenbaum. "Striatal Versus Hippocampal Representations During Win-Stay Maze Performance." Journal of Neurophysiology 101, no. 3 (March 2009): 1575–87. http://dx.doi.org/10.1152/jn.91106.2008.

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The striatum and hippocampus are widely held to be components of distinct memory systems that can guide competing behavioral strategies. However, some electrophysiological studies have suggested that neurons in both structures encode spatial information and may therefore make similar contributions to behavior. In rats well trained to perform a win-stay radial maze task, we recorded simultaneously from dorsal hippocampus and from multiple striatal subregions, including both lateral areas implicated in motor responses to cues and medial areas that work cooperatively with hippocampus in cognitive operations. In each brain region, movement through the maze was accompanied by the continuous sequential activation of sets of projection neurons. Hippocampal neurons overwhelmingly were active at a single spatial location (place cells). Striatal projection neurons were active at discrete points within the progression of every trial—especially during choices or following reward delivery—regardless of spatial position. Place-cell–type firing was not observed even for medial striatal cells entrained to the hippocampal theta rhythm. We also examined neural coding in earlier training sessions, when rats made use of spatial working memory to guide choices, and again found that striatal cells did not show place-cell–type firing. Prospective or retrospective encoding of trajectory was not observed in either hippocampus or striatum, at either training stage. Our results indicate that, at least in this task, dorsal hippocampus uses a spatial foundation for information processing that is not substantially modulated by spatial working memory demands. By contrast, striatal cells do not use such a spatial foundation, even in medial subregions that cooperate with hippocampus in the selection of spatial strategies. The progressive dominance of a striatum-dependent strategy does not appear to be accompanied by large changes in striatal or hippocampal single-cell representations, suggesting that the conflict between strategies may be resolved elsewhere.

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Saxena, Shobhit, Abdul Rawoof Pinjari, Ananya Roy, and Rajesh Paleti. "Multiple discrete-continuous choice models with bounds on consumptions." Transportation Research Part A: Policy and Practice 149 (July 2021): 237–65. http://dx.doi.org/10.1016/j.tra.2021.03.016.

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Han, Sang Pil, Sungho Park, and Wonseok Oh. "Mobile App Analytics: A Multiple Discrete-Continuous Choice Framework." MIS Quarterly 40, no. 4 (April 4, 2016): 983–1008. http://dx.doi.org/10.25300/misq/2016/40.4.09.

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Castro, Marisol, Chandra R. Bhat, Ram M. Pendyala, and Sergio R. Jara-Díaz. "Accommodating multiple constraints in the multiple discrete–continuous extreme value (MDCEV) choice model." Transportation Research Part B: Methodological 46, no. 6 (July 2012): 729–43. http://dx.doi.org/10.1016/j.trb.2012.02.005.

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Jäggi, Boris, Claude Weis, and Kay W. Axhausen. "Stated response and multiple discrete-continuous choice models: Analyses of residuals." Journal of Choice Modelling 6 (March 2013): 44–59. http://dx.doi.org/10.1016/j.jocm.2013.04.005.

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Bhat, Chandra R. "A new flexible multiple discrete–continuous extreme value (MDCEV) choice model." Transportation Research Part B: Methodological 110 (April 2018): 261–79. http://dx.doi.org/10.1016/j.trb.2018.02.011.

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Sikder, Sujan, and Abdul Rawoof Pinjari. "The benefits of allowing heteroscedastic stochastic distributions in multiple discrete-continuous choice models." Journal of Choice Modelling 9 (December 2013): 39–56. http://dx.doi.org/10.1016/j.jocm.2013.12.003.

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Pinjari, Abdul Rawoof. "Generalized extreme value (GEV)-based error structures for multiple discrete-continuous choice models." Transportation Research Part B: Methodological 45, no. 3 (March 2011): 474–89. http://dx.doi.org/10.1016/j.trb.2010.09.004.

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Bhat, Chandra R., Marisol Castro, and Mubassira Khan. "A new estimation approach for the multiple discrete–continuous probit (MDCP) choice model." Transportation Research Part B: Methodological 55 (September 2013): 1–22. http://dx.doi.org/10.1016/j.trb.2013.04.005.

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Mondal, Aupal, and Chandra R. Bhat. "A new closed form multiple discrete-continuous extreme value (MDCEV) choice model with multiple linear constraints." Transportation Research Part B: Methodological 147 (May 2021): 42–66. http://dx.doi.org/10.1016/j.trb.2021.03.005.

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Jäggi, Boris, Alexander Erath, Christoph Dobler, and Kay W. Axhausen. "Modeling Household Fleet Choice as Function of Fuel Price by Using a Multiple Discrete–Continuous Choice Model." Transportation Research Record: Journal of the Transportation Research Board 2302, no. 1 (January 2012): 174–83. http://dx.doi.org/10.3141/2302-19.

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Ma, Jie, Xin Ye, and Abdul Rawoof Pinjari. "Practical Method to Simulate Multiple Discrete-Continuous Generalized Extreme Value Model: Application to Examine Substitution Patterns of Household Transportation Expenditures." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 8 (April 16, 2019): 145–56. http://dx.doi.org/10.1177/0361198119842819.

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The multiple discrete-continuous generalized extreme value (MDCGEV) model has been derived from multivariate extreme value (MEV)-based stochastic specifications to relax the independence assumption in the multiple discrete-continuous extreme value (MDCEV) model. It is analogous to the situation where a generalized extreme value (GEV) model relaxes the same assumption in a multinomial logit (MNL) model. However, unlike the case of single discrete choice model where substitution patterns can be understood based on elasticity expressions for a change in the value of an explanatory variable, the MDCEV and its variants do not offer closed-form elasticity expressions. The predictions must be compared explicitly under the base case and policy case scenarios. To perform a prediction exercise with MDCEV or its variants, random samples have to be drawn from the relevant stochastic distributions, which is actually not a straightforward task. In this paper, a practical method is proposed for drawing from an MEV distribution and the method is demonstrated to examine substitution patterns in an MDCGEV model for household transportation expenditures. The empirical results show that the cross-elasticities of explanatory variables in the MDCGEV model exhibit more variations than those in MDCEV and multiple discrete-continuous nested extreme value (MDCNEV) models.

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Chen, Qun, and Feng Shi. "Model for Microcirculation Transportation Network Design." Mathematical Problems in Engineering 2012 (2012): 1–11. http://dx.doi.org/10.1155/2012/379867.

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The idea of microcirculation transportation was proposed to shunt heavy traffic on arterial roads through branch roads. The optimization model for designing micro-circulation transportation network was developed to pick out branch roads as traffic-shunting channels and determine their required capacity, trying to minimize the total reconstruction expense and land occupancy subject to saturation and reconstruction space constraints, while accounting for the route choice behaviour of network users. Since micro-circulation transportation network design problem includes both discrete and continuous variables, a discretization method was developed to convert two groups of variables (discrete variables and continuous variables) into one group of new discrete variables, transforming the mixed network design problem into a new kind of discrete network design problem with multiple values. The genetic algorithm was proposed to solve the new discrete network design problem. Finally a numerical example demonstrated the efficiency of the model and algorithm.

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Branch, Trevor A. "Reply to the comment by Francis on “Differences in predicted catch composition between two widely used catch equation formulations”Appears in Can. J. Fish. Aquat. Sci. 66: 126–132." Canadian Journal of Fisheries and Aquatic Sciences 67, no. 4 (April 2010): 766–68. http://dx.doi.org/10.1139/f10-024.

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Francis (2010. Can. J. Fish. Aquat. Sci. 67: 763–765) writes a thoughtful response detailing concerns with my suggestion that the continuous (Baranov) catch formulation is preferable to the discrete catch formulation when fishing mortality is high (T.A. Branch. 2009. Can. J. Fish. Aquat. Sci. 66: 126–132). He suggests the discrete formulation allows for multiple gear encounters and that formulation choice should depend on which formulation better fits the data. Here I first distinguish between gear selectivity and availability and then show that our two views are complementary: the original assumes fish groups with differing gear selectivity but full availability, whereas Francis assumes fish groups fully selected by fishing gear but with differing availability. I maintain that the discrete formulation only models a single instantaneous interaction between fish and fishing gear and therefore only part of the population can be caught if fish groups have equal gear selectivity that is less than 100%, whereas under the same assumptions, the continuous formulation would allow the entire population to be caught. Finally, when the balance between gear selectivity and availability is unknown, I agree that formulation choice could be driven by model fits to the data, although formulation choice could also be based on how the fishery operates.

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Astroza, Sebastian, Abdul Rawoof Pinjari, Chandra R. Bhat, and Sergio R. Jara-Díaz. "A Microeconomic Theory–Based Latent Class Multiple Discrete–Continuous Choice Model of Time Use and Goods Consumption." Transportation Research Record: Journal of the Transportation Research Board 2664, no. 1 (January 2017): 31–41. http://dx.doi.org/10.3141/2664-04.

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Jian, Sisi, Taha Hossein Rashidi, and Vinayak Dixit. "An analysis of carsharing vehicle choice and utilization patterns using multiple discrete-continuous extreme value (MDCEV) models." Transportation Research Part A: Policy and Practice 103 (September 2017): 362–76. http://dx.doi.org/10.1016/j.tra.2017.06.012.

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Van Nostrand, Caleb, Vijayaraghavan Sivaraman, and Abdul Rawoof Pinjari. "Analysis of long-distance vacation travel demand in the United States: a multiple discrete–continuous choice framework." Transportation 40, no. 1 (April 5, 2012): 151–71. http://dx.doi.org/10.1007/s11116-012-9397-6.

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Ahn, Jiwoon, Gicheol Jeong, and Yeonbae Kim. "A forecast of household ownership and use of alternative fuel vehicles: A multiple discrete-continuous choice approach." Energy Economics 30, no. 5 (September 2008): 2091–104. http://dx.doi.org/10.1016/j.eneco.2007.10.003.

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Augustin, Bertho, Abdul R. Pinjari, Naveen Eluru, and Ram M. Pendyala. "Estimation of Annual Mileage Budgets for a Multiple Discrete-Continuous Choice Model of Household Vehicle Ownership and Utilization." Transportation Research Record: Journal of the Transportation Research Board 2493, no. 1 (January 2015): 126–35. http://dx.doi.org/10.3141/2493-14.

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Branch, Trevor A. "Differences in predicted catch composition between two widely used catch equation formulations." Canadian Journal of Fisheries and Aquatic Sciences 66, no. 1 (January 2009): 126–32. http://dx.doi.org/10.1139/f08-196.

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Fishing gear selectivity varies among different types of fish (e.g., species, age, sex, or length groups), but their relative catch composition also depends on the fishing process. The continuous (Baranov) formulation assumes that fishing mortality and natural mortality occur together during the fishing season and that there are multiple encounters between fish and fishing gear. For this formulation, predicted catch composition depends on fishing mortality, and at high fishing mortality levels the entire population can be caught provided the selectivity is nonzero for all age groups. In contrast, the discrete formulation assumes that fishing mortality occurs separately from natural mortality and that fish encounter at most only one set of fishing gear. The discrete formulation is easier to compute, but the predicted catch composition is independent of fishing mortality, and some of the population remains unexploitable. The correct choice of equations depends on the particular fishery and fishing mortality levels; at low fishing mortality levels the predictions differ little, but at high fishing mortality levels where multiple gear encounters could occur, the continuous formulation is preferable.

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Makriyannis, Christos, Robert J. Johnston, and Adam W. Whelchel. "Are Choice Experiment Treatments of Outcome Uncertainty Sufficient? An Application to Climate Risk Reductions." Agricultural and Resource Economics Review 47, no. 3 (April 10, 2018): 419–51. http://dx.doi.org/10.1017/age.2017.27.

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Choice experiments addressing outcome uncertainty (OU) typically reframe continuous probability densities for each risky outcome into two discrete categories, each with a single probability of occurrence. The implications of this simplification for welfare estimation are unknown. This article evaluates the convergent validity of willingness-to-pay (WTP) estimates from a more accurate multiple-outcome treatment of OU, compared to the two-outcome approach. Results for a case study of coastal flood adaptation in Connecticut, United States, suggest that higher-resolution OU treatments increase choice complexity but can provide additional information on risk preferences and WTP. This tradeoff highlights challenges facing the valuation of uncertain outcomes.

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Renner, Philipp, and Karl Schmedders. "Discrete‐time dynamic principal–agent models: Contraction mapping theorem and computational treatment." Quantitative Economics 11, no. 4 (2020): 1215–51. http://dx.doi.org/10.3982/qe960.

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We consider discrete‐time dynamic principal–agent problems with continuous choice sets and potentially multiple agents. We prove the existence of a unique solution for the principal's value function only assuming continuity of the functions and compactness of the choice sets. We do this by a contraction mapping theorem and so also obtain a convergence result for the value function iteration. To numerically compute a solution for the problem, we have to solve a collection of static principal–agent problems at each iteration. As a result, in the discrete‐time setting solving the static problem is the difficult step. If the agent's expected utility is a rational function of his action, then we can transform the bi‐level optimization problem into a standard nonlinear program. The final results of our solution method are numerical approximations of the policy and value functions for the dynamic principal–agent model. We illustrate our solution method by solving variations of two prominent social planning models from the economics literature.

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Zheng, Kangning, Enjian Yao, and Yongsheng Zhang. "A joint model of household time use and task assignment for elderly couples with multiple constraints." PLOS ONE 16, no. 3 (March 11, 2021): e0247187. http://dx.doi.org/10.1371/journal.pone.0247187.

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Household time-use patterns are expected to reflect each household member’s daily activity participation and duration with intra-household interactions constrained by multiple budgets. Among various activities, the allocated activity derived from undertaking a household task is studied relatively less in the literature. Who will take an allocated activity is a discrete choice problem of household task assignment, and once a household member is assigned with one household task, other members will have more time to do other activities. To better understand household time-use patterns affected by household task assignment, this paper proposed a joint household-level multiple discrete-continuous extreme value-multinomial logit (MDCEV-MNL) model with multiple constraints. The Karush-Kuhn-Tucker (KKT) method combined with the simulation-based maximum likelihood estimation method is proposed to estimate the proposed model. Based on the household activity-travel data from Beijing of China, the proposed model is customized to explore elderly couples’ time-use patterns with intra-household interactions affected by household task assignment. Following the findings, policy implications are suggested to build an age-friendly society.

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Szkaliczki, Tibor. "Discrete Data Rate Adaptation for Wireless Body Area Networks." Applied Sciences 13, no. 14 (July 24, 2023): 8529. http://dx.doi.org/10.3390/app13148529.

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eHealth services require continuous data streaming and a stable level of quality of service. However, wireless network connections can be characterized by variable bandwidths. This requires continuous adaptation of systems, including adapting the bit rates of data streamed by sensors. Assigning appropriate rates to the data represents a main task in congestion control. Most of the current methods look for proper sensor data rates within continuous domains. We examine the case when sensors can generate data streams with several different qualities (e.g., sampling rates, sampling accuracies, etc.). For this reason, the domain of the data rate values can be restricted to the discrete values representing the data rates of the possible quality variations. This paper examines the optimization of the utility of the delivered data under resource constraints by selecting an appropriate variation of the provided data from a discrete set. We provide a formal model for delivering data streams in WBANs and recommend an optimization algorithm to solve the problem. Our recommended solutions are related to the multiple-choice multidimensional knapsack problem. By comparing the proposed algorithms, we found that the greedy method closely approximates the optimum in a short running time.

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Wang, Xinyi, and Sung Hoo Kim. "Prediction and Factor Identification for Crash Severity: Comparison of Discrete Choice and Tree-Based Models." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 9 (May 9, 2019): 640–53. http://dx.doi.org/10.1177/0361198119844456.

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Crash severity is one of the most widely studied topics in traffic safety area. Scholars have studied crash severity through various types of models. Using the publicly available 2017 Maryland crash data from the Department of Maryland State Police, the authors develop a multinomial logit (MNL) model and a random forest (RF) model, which belong to discrete choice and tree-based models, respectively, to (1) identify factors contributing to crash severity and (2) compare prediction performances and interpretation abilities between the two models. Based on the model results, major contributing factors of crash severity are identified, including collision type, occupant age, and speed limit. For the given dataset, RF has a higher prediction accuracy than MNL based on multiple measures (precision, recall, and F1 score), even though the differences are not dramatic. Sensitivity analysis results show that RF is less sensitive than MNL. RF can automatically capture the non-linear effects of continuous variables and reduce the influence of collinearity relationships existing among explanatory variables. This study shows the possibility of conducting sensitivity analysis to enhance understanding of MNL and RF results, and uncovers unique characteristics of the discrete choice and tree-based models.

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Bhat, Chandra R., Aupal Mondal, Abdul Rawoof Pinjari, Shobhit Saxena, and Ram M. Pendyala. "A multiple discrete continuous extreme value choice (MDCEV) model with a linear utility profile for the outside good recognizing positive consumption constraints." Transportation Research Part B: Methodological 156 (February 2022): 28–49. http://dx.doi.org/10.1016/j.trb.2021.12.013.

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Kuriyama, Koichi, Yasushi Shoji, and Takahiro Tsuge. "The value of leisure time of weekends and long holidays: The multiple discrete–continuous extreme value (MDCEV) choice model with triple constraints." Journal of Choice Modelling 37 (December 2020): 100238. http://dx.doi.org/10.1016/j.jocm.2020.100238.

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Saxena, Shobhit, Abdul Rawoof Pinjari, and Chandra R. Bhat. "Multiple discrete-continuous choice models with additively separable utility functions and linear utility on outside good: Model properties and characterization of demand functions." Transportation Research Part B: Methodological 155 (January 2022): 526–57. http://dx.doi.org/10.1016/j.trb.2021.11.011.

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Cui, Jiarui, Shuo Yang, and Dinghui Chen. "High-Frequency Time Series Data Regression Based on the Functional Bayesian Model Averaging." Highlights in Science, Engineering and Technology 49 (May 21, 2023): 76–83. http://dx.doi.org/10.54097/hset.v49i.8449.

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Regression analysis of high-frequency time series data has been an important problem in the field of statistical learning. In this paper, we propose a novel approach based on multiple basis function expansions and Bayesian model averaging when the predictor variable is a high-frequency time series and the response variable is continuous scalar data. On the one hand, the proposed method avoids the curse of dimensionality and extracts the functional information of the original sequence by transforming the discrete data into continuous functions in a function space consisting of some fixed basis functions. On the other hand, for the choice of basis functions, this paper proposes to adaptively determine the optimal solution using Bayesian model averaging, effectively balancing the variance and bias of the predictive model. The real data analysis shows that the proposed method has smaller mean squared error and absolute error, and is robust compared to other methods. Finally, the proposed method can be further extended to time series data applications such as weather forecasting and stock price prediction.

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Юрков, В., and V. Yurkov. "Approximation of Linear Sets in the Plane." Geometry & Graphics 7, no. 3 (December 2, 2019): 60–69. http://dx.doi.org/10.12737/article_5dce6cf7ae1d70.85408915.

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A few general lines in the ordinary Euclidean plane are said to be line generators of a plane linear set. To be able to say that every line of the set belongs to one-parametrical line set we have to find their envelope. We thus create a pencil of lines. In this article it will be shown that there are a finite number of pencils in one linear set. To find a pencil of lines the linear parametrical approximation is applied. Almost all of problems concerning the parametrical approximation of figure sets are well known and deeply developed for any point sets. The problem of approximation for non-point sets is an actual one. The aim of this paper is to give a path to parametrical approximation of linear sets defined in plane. The sets are discrete and consist of finite number of lines without any order. Each line of the set is given as y = ax + b. Parametrical approximation means a transformation the discrete set of lines into completely continuous family of lines. There are some problems. 1. The problem of order. It is necessary to represent the chaotic set of lines as well-ordered one. The problem is solved by means of directed circuits. Any of chaotic sets has a finite number of directed circuits. To create an order means to find all directed circuits in the given set. 2. The problem of choice. In order to find the best approximation, for example, the simplest one it is necessary to choose the simplest circuit. Some criteria of the choice are discussed in the paper. 3. Interpolation the set of line factors. A direct approach would simply construct an interpolation for all line factors. But this can lead to undesirable oscillations of the line family. To eliminate the oscillations the special factor interpolation are suggested. There are linear sets having one or several multiple points, one or several multiple lines and various combinations of multiple points and lines. Some theorems applied to these cases are formulated in the paper.

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Kokonendji, Célestin C., and Sobom M. Somé. "Bayesian Bandwidths in Semiparametric Modelling for Nonnegative Orthant Data with Diagnostics." Stats 4, no. 1 (March 4, 2021): 162–83. http://dx.doi.org/10.3390/stats4010013.

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Multivariate nonnegative orthant data are real vectors bounded to the left by the null vector, and they can be continuous, discrete or mixed. We first review the recent relative variability indexes for multivariate nonnegative continuous and count distributions. As a prelude, the classification of two comparable distributions having the same mean vector is done through under-, equi- and over-variability with respect to the reference distribution. Multivariate associated kernel estimators are then reviewed with new proposals that can accommodate any nonnegative orthant dataset. We focus on bandwidth matrix selections by adaptive and local Bayesian methods for semicontinuous and counting supports, respectively. We finally introduce a flexible semiparametric approach for estimating all these distributions on nonnegative supports. The corresponding estimator is directed by a given parametric part, and a nonparametric part which is a weight function to be estimated through multivariate associated kernels. A diagnostic model is also discussed to make an appropriate choice between the parametric, semiparametric and nonparametric approaches. The retention of pure nonparametric means the inconvenience of parametric part used in the modelization. Multivariate real data examples in semicontinuous setup as reliability are gradually considered to illustrate the proposed approach. Concluding remarks are made for extension to other multiple functions.

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Kocak, Salih. "Rheological Characterization of Ground Tire Rubber Modified Asphalt Binders with Parallel Plate and Concentric Cylinder Geometries." Sustainability 15, no. 4 (February 5, 2023): 2880. http://dx.doi.org/10.3390/su15042880.

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Recently, scrap tire rubber-modified asphalt binders and pavements have been the preferred choice of state DOTs and parties involved due to the desirable engineering, as well as economic and environmental impacts. Rheological and mechanical properties of rubber modifications have been the main focus of researchers for the last couple of decades. This paper investigates the rutting potential, fatigue cracking resistance, and continuous performance grade (CPG) changes of waste tire rubber-modified, original, and aged asphalt binders. The CPG of asphalt binders is determined at high, intermediate, and low temperatures. A Delta T Critical comparison of the binder was carried out to establish a relationship between measured parameters. Linear amplitude sweep (LAS) tests at equi-stiffness temperatures were conducted to discover the fatigue life of all binders while the multiple stress creep recovery test is performed to assess the high-temperature rutting performance of asphalt binders as per the Superpave performance grading system at accepted regional (58 °C) as well as high PG temperatures. In addition, parallel-plate geometry and concentric cylinder geometry were used with the Multiple Stress Creep Recovery (MSCR) test to discover the impact of discrete particles available in crumb/ground tire rubber-modified asphalt binders as per standards. The results show that rubber modifications improved the base binder’s rutting resistance and continuous PGs without adversely affecting the fatigue cracking resistance. Based on the mathematical expressions developed, 2.71%, 7.82%, 12.94%, and 18.05% (by weight of binder), GTR modifications improved the high PG of the modified binders one, two, three, and four grade bumps, respectively. Similar linear correlations with R2 0.872 and 0.6 were established for continuous low and intermediate PGs, respectively. MSCR test results revealed that both 9% and 20% GTR modifications were achieved to enhance the H-grade traffic level of the original binder to E-grade.

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Kudryashova, Anastasia Yu. "Development of a program for calculating additional distortions for various models of errors." T-Comm 16, no. 1 (2022): 51–58. http://dx.doi.org/10.36724/2072-8735-2022-16-1-51-58.

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When transmitting signals from a source to a receiver, their multiple transformations take place. At the same time, various types of spaces bijection in which signals are displayed allow minimizing additional distortions arising from errors in a discrete communication channel, or reducing the probability of a bit error when distortions occur in a continuous communication channel. This optimization of the choice of the bijection type is largely determined by the error model or, respectively, by the model of the acting noise, which cannot always be displayed in the form of an analytical expression, with the help of which the necessary transformations and calculations can be carried out in the future. In this regard, it is advisable to develop a software model in which it is possible to specify various types of errors, for which further calculations of the optimal types of spaces bijection that minimize the probability of bit errors, or, accordingly, the amount of additional distortions, can be carried out. This article discusses the problems associated with evaluating the efficient coding of a signal source. For this, an algorithm and a program for evaluating the effective coding of a signal source for the currently widely used analog-to digital conversion of a continuous signal into a binary signal are proposed. The results of this study will be useful in this in the implementation of the optimization of the arising distortions taking into account all influencing factors in the system as a whole.

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Calastri, Chiara, Stephane Hess, Andrew Daly, and Juan Antonio Carrasco. "Does the social context help with understanding and predicting the choice of activity type and duration? An application of the Multiple Discrete-Continuous Nested Extreme Value model to activity diary data." Transportation Research Part A: Policy and Practice 104 (October 2017): 1–20. http://dx.doi.org/10.1016/j.tra.2017.07.003.

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Hamed, Mohammad M., and Walid M. Abdelwahab. "Effect of government policies and vehicle marketing strategies on household vehicle demand and fuel consumption." Canadian Journal of Civil Engineering 23, no. 3 (June 1, 1996): 587. http://dx.doi.org/10.1139/l96-867.

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The objective of this paper is to develop demand models to forecast household vehicle demand and corresponding fuel consumption in Jordan. Understanding the factors that influence household vehicle quantity holdings provides a useful tool for developing strategies aimed at curtailing the contribution of automobiles towards environmental pollution, traffic congestion, and traffic accidents in urban areas. The demand for automobile and fuel by a household is simultaneously estimated by a joint discrete and continuous choice model. A multinomial logit model is used to examine the number of vehicles owned by a household, whereas a multiple regression model is used to predict the amount of fuel consumed. A random sample of households from the Greater Amman area is used to estimate demand and choice models. Results suggest that the socioeconomic characteristics of a household, government policies relating to vehicle import duties and vintage, and private sector marketing strategies, all influence a household's decision on the number of vehicles owned. Results strongly show that households with different vehicle ownership levels respond differently to government policies and car dealers' marketing strategies. Policy makers and transportation planners can use the results of this study to forecast the expected demand for used cars, and the increase in the number of new cars, given a set of government and private sector strategies. The results also can be used to predict fuel demand at various levels of household vehicle ownership. Transportation planners can also use these results to assist in formulating strategies regarding urban road network improvements, and future demand for public transportation. Key words: vehicle ownership, fuel consumption, logit model, government policy.

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Paparrizos, John, Paul Boniol, Themis Palpanas, Ruey S. Tsay, Aaron Elmore, and Michael J. Franklin. "Volume under the surface." Proceedings of the VLDB Endowment 15, no. 11 (July 2022): 2774–87. http://dx.doi.org/10.14778/3551793.3551830.

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Anomaly detection (AD) is a fundamental task for time-series analytics with important implications for the downstream performance of many applications. In contrast to other domains where AD mainly focuses on point-based anomalies (i.e., outliers in standalone observations), AD for time series is also concerned with range-based anomalies (i.e., outliers spanning multiple observations). Nevertheless, it is common to use traditional point-based information retrieval measures, such as Precision, Recall, and F-score, to assess the quality of methods by thresholding the anomaly score to mark each point as an anomaly or not. However, mapping discrete labels into continuous data introduces unavoidable shortcomings, complicating the evaluation of range-based anomalies. Notably, the choice of evaluation measure may significantly bias the experimental outcome. Despite over six decades of attention, there has never been a large-scale systematic quantitative and qualitative analysis of time-series AD evaluation measures. This paper extensively evaluates quality measures for time-series AD to assess their robustness under noise, misalignments, and different anomaly cardinality ratios. Our results indicate that measures producing quality values independently of a threshold (i.e., AUC-ROC and AUC-PR) are more suitable for time-series AD. Motivated by this observation, we first extend the AUC-based measures to account for range-based anomalies. Then, we introduce a new family of parameter-free and threshold-independent measures, VUS (Volume Under the Surface), to evaluate methods while varying parameters. Our findings demonstrate that our four measures are significantly more robust in assessing the quality of time-series AD methods.

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Zhang, Yiqi, and Changxu Wu. "Modeling the Effects of Warning Lead Time, Warning Reliability and Warning Style on Human Performance Under Connected Vehicle Settings." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (September 2018): 701. http://dx.doi.org/10.1177/1541931218621158.

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Deaths and injuries resulted from traffic accidents is still a major public health problem. Recent advances in connected vehicle technology support a connected driving environment in which vehicles are enabled to communicate with each other and with roadside infrastructures via Dedicated Short Range Communication (DSRC). Connected vehicle safety applications supported by this technology allow drivers to learn about the traffic situations out of their sight and ahead of time so that drivers are warned early enough to make proper responses. As the connected vehicle systems (CVS) are designed with an aim to improving driver safety, the effectiveness of the CVS can not be achieved without drivers making proper responses in responding to the wireless warnings. Therefore, it is essential to understand and model the mechanism for human processing and responding to warnings from connected vehicle systems, and apply the driver model to optimize the design the CVS at the interface level and the communication level. Queuing Network-Model Human Processor (QN-MHP) is a computational framework that integrates three discrete serial stages of human information processing (i.e., perceptual, cognitive, and motor processing) into three continuous subnetworks. Each subnetwork is constructed of multiple servers and links among these servers. Each individual server is an abstraction of a brain area with specific functions, and links among servers represent neural pathways among functional brain areas. The neurological processing of stimuli is illustrated in the transformation of entities passing through routes in QN-MHP. Since this architecture was established, QN-MHP has been applied to quantify various aspects of aspects of driver behavior and performance, including speed control (Bi & Liu, 2009; Zhao & Wu, 2013b), lateral control (Bi et al., 2012; Bi et al., 2013), driver distraction (Bi et al., 2012; Fuller, Reed & Liu, 2012; Liu, Feyen & Tsimhoni, 2006), and driver workload (Wu & Liu, 2007; Wu et al., 2008). Most of the driver model built upon QN-MHP focused on the modeling of driver performance in normal driving situation. In a previous work of authors, a mathematical model was developed to predict the effects of warning loudness, word choice, and lead time on drivers’ warning reaction time (Zhang, Wu, & Wan, 2016). The current research focused on the development of a mathematical model based on QN-MHP to quantify and predict driver performance in responding to warnings from connected vehicle systems, including warning response time and the selection of warning response type. The model also quantified the effects of important warning characteristics in connected vehicle systems, including warning reliability, warning lead time, and speech warning style. The model was validated via an experimental study indicating its good predictability of driver behavior and performance in connected vehicle systems. In particular, the model was able to explain 68.83% of the warning response type in the initial trial of the experiment with a root mean square error (RMSE) of 0.18. By adding the warning effect on the probability of a response type through trials, the model was able to explain 65.13% of the warning response type in the initial trial of the experiment with a root mean square error (RMSE) of 0.16. In terms of warning response time, the model prediction of warning response time under different warning reliability, style and lead time were very similar to the response time results from the experiments. The model was able to explain 88.30% of the experimental response time in average with a root mean square error (RMSE) of 0.16s. The developed driver model could be applied to optimize the design of the connected vehicle systems based on driver

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Franceschinis, Cristiano, Riccardo Scarpa, Luca Rossetto, and Mara Thiene. "Is local and organic produce less satiating? Some evidence from a field experiment." European Review of Agricultural Economics, July 11, 2022. http://dx.doi.org/10.1093/erae/jbac014.

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Abstract We investigate consumers’ preferences towards local and organic food via a framed field experiment involving revealed multiple discrete–continuous choices. Participants were endowed with a cash amount as a budget to purchase any desired quantity of different products. We modelled choices via the multiple discrete–continuous nested extreme value model. Central to our investigation is the test of the hypothesis of the constant effect of attitudes across consumption doses, which is normally an assumption invoked a priori and without testing in discrete choice analyses. Our results support the hypothesis and reveal a strong preference towards organic and local products, associated with both the highest baseline utility and the lowest satiation effect.

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Pellegrini, Andrea, Igor Sarman, and Rico Maggi. "Understanding tourists’ expenditure patterns: a stochastic frontier approach within the framework of multiple discrete–continuous choices." Transportation, February 6, 2020. http://dx.doi.org/10.1007/s11116-020-10083-2.

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Mesaric, Raphael, Aupal Mondal, Katie Asmussen, Joseph Molloy, Chandra R. Bhat, and Kay W. Axhausen. "Impact of the COVID-19 Pandemic on Activity Time Use and Timing Behavior in Switzerland." Transportation Research Record: Journal of the Transportation Research Board, May 5, 2022, 036119812210872. http://dx.doi.org/10.1177/03611981221087233.

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This paper analyzes the impact of the COVID-19 pandemic on activity time use and timing behavior in Switzerland. The evaluation is based on mobility tracking data collected in Switzerland during the COVID-19 pandemic. The pandemic has affected how people spend their time and schedule their activities throughout the day, subsequently creating new activity patterns. Because of the rare occurrences of pandemics in the recent past, little is known about their implications on the behavioral choices of affected people. This paper analyzes these implications by applying a multiple discrete-continuous choice model on mobility tracking data from Switzerland. The applied model is consistent with the results of the descriptive analysis and shows that the different stages of the pandemic drove changes in the activity patterns. During the lockdown, an increase in home activities comes along with decreases in the other activity types. With progressive relaxation of the measures in the following phases, the trends slowly return to the initial state before the pandemic. In addition, it can be seen that the impact of main drivers such as age, gender, household size, income and weather on time use and activity scheduling varies between phases, activity types, and time of day.

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Daniel, Aemiro Melkamu. "Household Fuel Choice and Use: A Multiple Discrete-Continuous Framework." SSRN Electronic Journal, 2020. http://dx.doi.org/10.2139/ssrn.3562270.

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Pellegrini, Andrea, John Rose, and Riccardo Scarpa. "Multiple herbicide use in cropland: A discrete continuous model for stated choice data." Land Economics, November 11, 2021, 092520–0150. http://dx.doi.org/10.3368/le.98.2.092520-0150r1.

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Chang, Jia Jia, Zhi Jun Hu, and Changxiu Liu. "Optimal contracting with asymmetric belief and complementarity." Kybernetes, January 12, 2023. http://dx.doi.org/10.1108/k-07-2022-0946.

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PurposeIn this study, a dynamic contracting model is developed between a venture capitalist (VC) and an entrepreneur (EN) to explore the influence of asymmetric beliefs regarding output-relevant parameters, agency conflicts and complementarity on the VC's posterior beliefs through the EN's unobservable effort choices to influence the optimal dynamic contract.Design/methodology/approachThe authors construct the contracting model by incorporating the VC's effort, which is ignored in most studies. Using backward induction and a discrete-time approximation approach, the authors solve the continuous-time contract design problem, which evolves into a nonlinear ordinary differential equation (ODE).FindingsThe optimal equity share that the VC provides to the EN decreases over time. In accordance with the empirical evidence, the EN's optimistic beliefs regarding the project's profitability positively affect its equity share. However, the interactions between the optimal equity share, project risk and both partners' degrees of risk aversion are not monotonic. Moreover, the authors find that the optimal equity share increases with the degree of complementarity, which indicates that the EN is willing to cooperate with the VC. This study’s results also show that the optimal equity shares at each time are interdependent if the VC is risk-averse and independent if the VC is risk-neutral.Research limitations/implicationsIn conclusion, the authors highlight two potential directions for future research. First, the authors only considered a single VC, whereas in practice, a risk project may be carried out by multiple VCs, and it is interesting to discuss how the degree of complementarity affects the number of VCs that ENs contract. Second, the authors may introduce jumps and consider more general multivariate stochastic volatility models for output dynamics and analyze the characteristics of the optimal contracts. Third, further research can deal with other forms of discretionary output functions concerning complementarity, such as Cobb–Douglas and constant elasticity of substitution (See Varian, 1992).Social implicationsThe results of this study have several implications. First, it offers a novel approach to designing dynamic contracts that are specific and easy to operate. To improve the complicated venture investment situation and abate conflict between contractual parties, this study plays a good reference role. Second, the synergy effect proposed in this study provides a theoretical explanation for the executive compensation puzzle in economics, in which managers are often “rewarded for luck” (Bertrand and Mullainathan, 2001; Wu et al., 2018). This result indicates a realistic perspective on financing and establishing cooperative relationships, which enhances the efficiency of venture investment. Third, from an empirical standpoint, one can apply this framework to study research and development (R&D) problems.Originality/valueFirst, the authors introduce asymmetric beliefs and Bayesian learning to study the dynamic contract design problem and discuss their effects on equity share. Second, the authors incorporate the VC's effort into the contracting problem, and analyze the synergistic effect of effort complementarity on the optimal dynamic contract.

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Journal articles on the topic 'Multiple discrete-continuous choices'

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