In this paper we develop a two-step survival time approach – a discrete logit model with survival time dummies – that allows for time-varying explanatory variables and interval censored data. Our empirical analysis reveals that the twostep approach outperforms the benchmark logit model with respect to out-ofsample prediction accuracy. Survival time, however, does not play an important role. The...

This paper investigates the potential of a cellular automata (CA) model based on logistic regression (logit) and Markov Chain Monte Carlo (MCMC) to simulate the dynamics of urban growth. The model assesses urbanization likelihood based on (i) a set of urban development driving forces (calibrated based on logit) and (ii) the land-use of neighboring cells (calibrated based on MCMC). An innovative...

We present a new multi-path routing methodology, MLBrouting, that is based on the multinomial logit model, which is well known in the random utility field. The key concept of the study is to set multiple paths from the origin to the destination, and distribute packets in accordance with multinomial logit type probability. Since MLB-routing is pure multi-path routing, it reduces the convergence ...

We report the results of an experiment designed to shed light on beliefs off equilibrium paths. The experiment implements an incomplete information club game. A unique outcome results in all perfect Bayesian equilibria, but beliefs and actions off the equilibrium path are unconstrained under all concepts except extensive form rationalizability (EFR) and logit equilibrium. 90% of subject’s decis...

Recently, the Markov chain choice model has been introduced by Blanchet et al. to overcome the computational intractability for learning and revenue management for several modern choice models, including the mixed multinomial logit models. However, the known methods for learning the Markov models require almost all items to be offered in the learning stage, which is impractical. To address this...

In the past, research in traffic assignment modeling has been directed primarily towards the deterministic model. Alternative, more behavioral principles were thought to be too demanding computationally. This paper presents two mathematical contributions that enable one to solve a logit assignment model with flow-dependent travel times at a reduced cost. First, a convergence test for Fisk's min...

We consider the problem of combining k subjective probability distributions for a quantity of interest θ ∈ Θ. Two modified versions of the irrelevance of alternatives axiom are introduced by focusing on the consensual conditional odds, rather than the consensual probabilities. A strong modification of the axiom requires that the consensual odds depend only on the individual odds, while a weak m...

In this paper, we propose a novel technique for direct recognition of multiple speech streams given the single channel of mixed speech, without first separating them. Our technique is based on permutation invariant training (PIT) for automatic speech recognition (ASR). In PIT-ASR, we compute the average cross entropy (CE) over all frames in the whole utterance for each possible output-target as...

Even when information is made available through public campaigns, people may still retain inaccurate perceptions of environmental quality. We look at coastal water quality in Southern California via a telephone survey. Fewer than half of respondents are able to correctly rank two randomly chosen beaches in terms of water quality. A logit analysis of the rankings reveals that there are systemati...

1. The Effect of Response Level Ordering on Parameter Estimate Interpretation 2. Odds Ratios 2.1 Binary Explanatory Variable Modeling the Event 2.2 Binary Explanatory Variable Modeling the Nonevent 2.3 Continuous Explanatory Variable 3. Predicted Probabilities 4. Predicted by Observed Classification Tables 4.1 Classification Using Predicted Probabilities 4.2 Classification Using Bias-adjusted P...