111,406 research outputs found
Methodological and empirical challenges in modelling residential location choices
The modelling of residential locations is a key element in land use and transport planning. There are significant empirical and methodological challenges inherent in such modelling, however, despite recent advances both in the availability of spatial datasets and in computational and choice modelling techniques.
One of the most important of these challenges concerns spatial aggregation. The housing market is characterised by the fact that it offers spatially and functionally heterogeneous products; as a result, if residential alternatives are represented as aggregated spatial units (as in conventional residential location models), the variability of dwelling attributes is lost, which may limit the predictive ability and policy sensitivity of the model. This thesis presents a modelling framework for residential location choice that addresses three key challenges: (i) the development of models at the dwelling-unit level, (ii) the treatment of spatial structure effects in such dwelling-unit level models, and (iii) problems associated with estimation in such modelling frameworks in the absence of disaggregated dwelling unit supply data. The proposed framework is applied to the residential location choice context in London.
Another important challenge in the modelling of residential locations is the choice set formation problem. Most models of residential location choices have been developed based on the assumption that households consider all available alternatives when they are making location choices. Due the high search costs associated with the housing market, however, and the limited capacity of households to process information, the validity of this assumption has been an on-going debate among researchers. There have been some attempts in the literature to incorporate the cognitive capacities of households within discrete choice models of residential location: for instance, by modelling households’ choice sets exogenously based on simplifying assumptions regarding their spatial search behaviour (e.g., an anchor-based search strategy) and their characteristics. By undertaking an empirical comparison of alternative models within the context of residential location choice in the Greater London area this thesis investigates the feasibility and practicality of applying deterministic choice set formation approaches to capture the underlying search process of households. The thesis also investigates the uncertainty of choice sets in residential location choice modelling and proposes a simplified probabilistic choice set formation approach to model choice sets and choices simultaneously.
The dwelling-level modelling framework proposed in this research is practice-ready and can be used to estimate residential location choice models at the level of dwelling units without requiring independent and disaggregated dwelling supply data. The empirical comparison of alternative exogenous choice set formation approaches provides a guideline for modellers and land use planners to avoid inappropriate choice set formation approaches in practice. Finally, the proposed simplified choice set formation model can be applied to model the behaviour of households in online real estate environments.Open Acces
Approval-Based Shortlisting
Shortlisting is the task of reducing a long list of alternatives to a
(smaller) set of best or most suitable alternatives from which a final winner
will be chosen. Shortlisting is often used in the nomination process of awards
or in recommender systems to display featured objects. In this paper, we
analyze shortlisting methods that are based on approval data, a common type of
preferences. Furthermore, we assume that the size of the shortlist, i.e., the
number of best or most suitable alternatives, is not fixed but determined by
the shortlisting method. We axiomatically analyze established and new
shortlisting methods and complement this analysis with an experimental
evaluation based on biased voters and noisy quality estimates. Our results lead
to recommendations which shortlisting methods to use, depending on the desired
properties
DISCRETE DEPENDENT VARIABLES: A GUIDE TO ALTERNATIVE ESTIMATING TECHNIQUES WITH AN ANNOTATIVE BIBLIOGRAPHY OF LOGIT ANALYSIS
Research Methods/ Statistical Methods,
A tutorial on recursive models for analyzing and predicting path choice behavior
The problem at the heart of this tutorial consists in modeling the path
choice behavior of network users. This problem has been extensively studied in
transportation science, where it is known as the route choice problem. In this
literature, individuals' choice of paths are typically predicted using discrete
choice models. This article is a tutorial on a specific category of discrete
choice models called recursive, and it makes three main contributions: First,
for the purpose of assisting future research on route choice, we provide a
comprehensive background on the problem, linking it to different fields
including inverse optimization and inverse reinforcement learning. Second, we
formally introduce the problem and the recursive modeling idea along with an
overview of existing models, their properties and applications. Third, we
extensively analyze illustrative examples from different angles so that a
novice reader can gain intuition on the problem and the advantages provided by
recursive models in comparison to path-based ones
Multicriteria ranking using weights which minimize the score range
Various schemes have been proposed for generating a set of non-subjective weights when aggregating multiple criteria for the purposes of ranking or selecting alternatives. The maximin approach chooses the weights which maximise the lowest score (assuming there is an upper bound to scores). This is equivalent to finding the weights which minimize the maximum deviation, or range, between the worst and best scores (minimax). At first glance this seems to be an equitable way of apportioning weight, and the Rawlsian theory of justice has been cited in its support.We draw a distinction between using the maximin rule for the purpose of assessing performance, and using it for allocating resources amongst the alternatives. We demonstrate that it has a number of drawbacks which make it inappropriate for the assessment of performance. Specifically, it is tantamount to allowing the worst performers to decide the worth of the criteria so as to maximise their overall score. Furthermore, when making a selection from a list of alternatives, the final choice is highly sensitive to the removal or inclusion of alternatives whose performance is so poor that they are clearly irrelevant to the choice at hand
Automatic estimation of flux distributions of astrophysical source populations
In astrophysics a common goal is to infer the flux distribution of
populations of scientifically interesting objects such as pulsars or
supernovae. In practice, inference for the flux distribution is often conducted
using the cumulative distribution of the number of sources detected at a given
sensitivity. The resulting "-" relationship can be used to
compare and evaluate theoretical models for source populations and their
evolution. Under restrictive assumptions the relationship should be linear. In
practice, however, when simple theoretical models fail, it is common for
astrophysicists to use prespecified piecewise linear models. This paper
proposes a methodology for estimating both the number and locations of
"breakpoints" in astrophysical source populations that extends beyond existing
work in this field. An important component of the proposed methodology is a new
interwoven EM algorithm that computes parameter estimates. It is shown that in
simple settings such estimates are asymptotically consistent despite the
complex nature of the parameter space. Through simulation studies it is
demonstrated that the proposed methodology is capable of accurately detecting
structural breaks in a variety of parameter configurations. This paper
concludes with an application of our methodology to the Chandra Deep Field
North (CDFN) data set.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS750 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
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