Zobrazeno 1 - 10
of 180
pro vyhledávání: '"Vij, Akshay"'
This study proposes a flexible and scalable single-level framework for origin-destination matrix (ODM) inference using data from IoT (Internet of Things) and other sources. The framework allows the analyst to integrate information from multiple data
Externí odkaz:
http://arxiv.org/abs/2211.10366
Autor:
Anilan, V., Vij, Akshay
Publikováno v:
In Transportation Research Part D November 2024 136
Autor:
Vij, Akshay, Souza, Flavio F., Barrie, Helen, Anilan, V., Sarmiento, Sergio, Washington, Lynette
Publikováno v:
In Journal of Economic Behavior and Organization October 2023 214:782-800
Publikováno v:
In Transportation Research Part A September 2023 175
In this paper, we contrast parametric and semi-parametric representations of unobserved heterogeneity in hierarchical Bayesian multinomial logit models and leverage these methods to infer distributions of willingness to pay for features of shared aut
Externí odkaz:
http://arxiv.org/abs/1907.09639
Autor:
Vij, Akshay
The transport sector is witnessing unprecedented levels of disruption. Privately owned cars that operate on internal combustion engines have been the dominant modes of passenger transport for much of the last century. However, recent advances in tran
Externí odkaz:
http://arxiv.org/abs/1904.05554
Autor:
Ardeshiri, Ali, Vij, Akshay
Issues such as urban sprawl, congestion, oil dependence, climate change and public health, are prompting urban and transportation planners to turn to land use and urban design to rein in automobile use. One of the implicit beliefs in this effort is t
Externí odkaz:
http://arxiv.org/abs/1902.01986
Autor:
Vij, Akshay, Krueger, Rico
Publikováno v:
Transportation Research Part B: Methodological, Volume 106, December 2017, Pages 76-101
This study proposes a mixed logit model with multivariate nonparametric finite mixture distributions. The support of the distribution is specified as a high-dimensional grid over the coefficient space, with equal or unequal intervals between successi
Externí odkaz:
http://arxiv.org/abs/1802.02299
We present a mixed multinomial logit (MNL) model, which leverages the truncated stick-breaking process representation of the Dirichlet process as a flexible nonparametric mixing distribution. The proposed model is a Dirichlet process mixture model an
Externí odkaz:
http://arxiv.org/abs/1801.06296
We provide a microeconomic framework for decision trees: a popular machine learning method. Specifically, we show how decision trees represent a non-compensatory decision protocol known as disjunctions-of-conjunctions and how this protocol generalize
Externí odkaz:
http://arxiv.org/abs/1711.04826