diff --git a/paper.bib b/paper.bib index 356c510..7bdbe38 100644 --- a/paper.bib +++ b/paper.bib @@ -1,10 +1,11 @@ @Article{Barbosa2018, - Title = {Human mobility: Models and applications}, - Author = {Barbosa, H. and Barthelemy, M. and Ghoshal, G. and James, C. R. and Lenormand, M. and Louail, T. and Menezes, R. and Ramasco, J. J. and Simini, F. and Tomasini, M.}, - Journal = {Physics Reports}, - Year = {2018}, - Pages = {1-74}, - Volume = {734} + author = {Barbosa, H. and Barthelemy, M. and Ghoshal, G. and James, C. R. and Lenormand, M. and Louail, T. and Menezes, R. and Ramasco, J. J. and Simini, F. and Tomasini, M.}, + journal = {Physics Reports}, + title = {Human mobility: Models and applications}, + year = {2018}, + pages = {1-74}, + volume = {734}, + doi = {10.1016/j.physrep.2018.01.001}, } @Article{Lenormand2016, @@ -14,49 +15,51 @@ @Article{Lenormand2016 year = {2016}, pages = {158-169}, volume = {51}, + doi = {10.1016/j.jtrangeo.2015.12.008}, } -@ARTICLE{Simini2012, - author = {Simini, F. and Gonz{\'{a}}lez, M. C. and Maritan, A. and Barabasi, - A.-L.}, - title = {A universal model for mobility and migration patterns}, +@Article{Simini2012, + author = {Simini, F. and Gonz{\'{a}}lez, M. C. and Maritan, A. and Barabasi, A.-L.}, journal = {Nature}, - year = {2012}, - volume = {484}, - pages = {96-100} + title = {A universal model for mobility and migration patterns}, + year = {2012}, + pages = {96-100}, + volume = {484}, + doi = {10.1038/nature10856}, } -@ARTICLE{Yang2014, - author = {Yang, Y. and Herrera, C. and Eagle, N. and Gonz{\'{a}}lez, M. C.}, - title = {Limits of Predictability in Commuting Flows in the Absence of Data - for Calibration}, +@Article{Yang2014, + author = {Yang, Y. and Herrera, C. and Eagle, N. and Gonz{\'{a}}lez, M. C.}, journal = {Scientific Reports}, - year = {2014}, - volume = {4}, - pages = {5662}, - number = {5662} + title = {Limits of Predictability in Commuting Flows in the Absence of Data for Calibration}, + year = {2014}, + number = {5662}, + pages = {5662}, + volume = {4}, + doi = {10.1038/srep05662}, } -@ARTICLE{Lenormand2012, - author = {Lenormand, M. and Huet, S. and Gargiulo, F. and Deffuant, G.}, - title = {A {U}niversal {M}odel of {C}ommuting {N}etworks}, - journal = {PLoS ONE}, - year = {2012}, - volume = {7}, - pages = {e45985}, - owner = {maxime.lenormand}, - timestamp = {2012.03.23} +@Article{Lenormand2012, + author = {Lenormand, M. and Huet, S. and Gargiulo, F. and Deffuant, G.}, + journal = {PLoS ONE}, + title = {A {U}niversal {M}odel of {C}ommuting {N}etworks}, + year = {2012}, + pages = {e45985}, + volume = {7}, + doi = {10.1371/journal.pone.0045985}, + owner = {maxime.lenormand}, + timestamp = {2012.03.23}, } -@ARTICLE{Masucci2013, - author = {Masucci, A. and Serras, Joan and Johansson, Anders and Batty, Michael}, - title = {Gravity versus radiation models: On the importance of scale and heterogeneity - in commuting flows}, +@Article{Masucci2013, + author = {Masucci, A. and Serras, Joan and Johansson, Anders and Batty, Michael}, journal = {Phys. Rev. E}, - year = {2013}, - volume = {88}, - pages = {022812}, - issue = {2} + title = {Gravity versus radiation models: On the importance of scale and heterogeneity in commuting flows}, + year = {2013}, + pages = {022812}, + volume = {88}, + doi = {10.1103/physreve.88.022812}, + issue = {2}, } @Article{Wolwer2018, @@ -67,6 +70,7 @@ @Article{Wolwer2018 number = {31}, pages = {1038}, volume = {3}, + doi = {10.21105/joss.01038}, } @Manual{Lovelace2023, diff --git a/paper.md b/paper.md index fc9e5da..190c82a 100644 --- a/paper.md +++ b/paper.md @@ -7,7 +7,7 @@ tags: - Commuting networks - Gravity model - Radiation model -date: "5 July 2023" +date: "25 July 2023" output: pdf_document authors: - name: "Maxime Lenormand" @@ -24,10 +24,11 @@ affiliations: Spatial interaction models are widely used to estimate and explain spatial interactions between geographical areas or locations. These models are usually based on the characteristics of the locations and the way they are -spatially distributed. Interactions between locations can take several forms, -population movements, widely studied in geography, transportation research and -urban planning is one of them. The flows of individuals between locations is -usually represented by a trip table better known as Origin-Destination (OD) +spatially distributed. Several forms of interaction can occur between locations, +one of which is population movements. This particular type of interaction is +widely examined in the fields of geography, transportation research, and +urban planning. The flows of individuals between locations is +usually represented by a trip table better known as an Origin-Destination (OD) matrix [@Lenormand2016;@Barbosa2018]. The estimation of OD matrices is part of the four-step travel model in transportation research. It corresponds to the second step, called trip distribution, the aim of which is to match the trip @@ -37,16 +38,16 @@ framework. In order to facilitate the use and comparison of trip distribution models, and more generally spatial distribution models, we present **TDML** an R package -proposing a set of easy-to-use functions to rigorously and fairly compare +providing a set of easy-to-use functions to rigorously and fairly compare trip distribution laws and models as described in @Lenormand2016. # Statement of need Trip distribution models are generally composed of two mechanisms, one mechanism -based on a 'law' to estimate the probability that an individual move from one +based on a 'law' to estimate the probability that an individual moves from one location to another and a second mechanism based on a 'model' used to estimate the number of individuals moving from one location to another. These two -mechanisms are rarely dissociated which could lead to methodological flaws when +mechanisms are rarely disentangled which could lead to methodological flaws when comparing different laws and/or models [@Lenormand2012;@Simini2012;@Masucci2013; @Yang2014]. This is particularly important when we compare the two historical approaches - gravity and intervening opportunities - for the estimation of @@ -69,16 +70,15 @@ of trip distribution laws more complicated for non-expert users. Furthermore, observed and simulated OD matrices. To overcome these limitations, the **TDML** R package is based on a two-step -approach to generate mobility flows by separating the trip distribution law, -gravity or intervening opportunities, from the modeling approach used to -generate the flows from this law. +approach to generate mobility flows by separating the trip distribution law +from the modeling approach used to generate the flows from this law. # Functionality **TDLM** is available on [CRAN](https://cran.r-project.org/package=TDLM) and [GitHub](https://github.com/EpiVec/TDLM/). The **TDLM**'s website includes a [tutorial](https://epivec.github.io/TDLM/articles/TDLM.html) describing the functions of this package with an illustrative example based on -commuting data from US Kansas in 2000. +commuting data from Kansas in the United States in 2000. **TDLM** features four main functions for generating OD matrices based on a wide range of trip distribution laws and models and for evaluating