Pub Date : 2018-01-02DOI: 10.1080/08898480.2017.1408354
L. Bartoli, Maria Chiara Pagliarella, C. Russo, Renato Salvatore
ABSTRACT The Fay-Herriot area-level model for correlated response data is augmented with a between-groups-of-domains effect. Correlated-response parameters of small-area estimates no longer need the assumption of spatial contiguity. A simulation shows that area-level correlated-response observations increase the efficiency of the estimates, but do not reduce the biases.
{"title":"Small-area estimation in the presence of area-level correlated responses","authors":"L. Bartoli, Maria Chiara Pagliarella, C. Russo, Renato Salvatore","doi":"10.1080/08898480.2017.1408354","DOIUrl":"https://doi.org/10.1080/08898480.2017.1408354","url":null,"abstract":"ABSTRACT The Fay-Herriot area-level model for correlated response data is augmented with a between-groups-of-domains effect. Correlated-response parameters of small-area estimates no longer need the assumption of spatial contiguity. A simulation shows that area-level correlated-response observations increase the efficiency of the estimates, but do not reduce the biases.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"25 1","pages":"20 - 40"},"PeriodicalIF":1.8,"publicationDate":"2018-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2017.1408354","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49663359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-02DOI: 10.1080/08898480.2017.1348723
N. Daskalova
ABSTRACT When proliferating cells are counted in several independent colonies at some time points, the maximum likelihood estimates of the parameters of the multitype branching process are obtained trough an expectation maximization algorithm. In the case of an offspring distribution governed by a Markov branching process with binary family trees, this method, relying then on a partial knowledge of the tree, yields the same estimates as those computed with the complete knowledge of the tree.
{"title":"Expectation maximization estimates of the offspring probabilities in a class of multitype branching processes with binary family trees","authors":"N. Daskalova","doi":"10.1080/08898480.2017.1348723","DOIUrl":"https://doi.org/10.1080/08898480.2017.1348723","url":null,"abstract":"ABSTRACT When proliferating cells are counted in several independent colonies at some time points, the maximum likelihood estimates of the parameters of the multitype branching process are obtained trough an expectation maximization algorithm. In the case of an offspring distribution governed by a Markov branching process with binary family trees, this method, relying then on a partial knowledge of the tree, yields the same estimates as those computed with the complete knowledge of the tree.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"24 1","pages":"246 - 256"},"PeriodicalIF":1.8,"publicationDate":"2017-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2017.1348723","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41520962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-02DOI: 10.1080/08898480.2017.1348718
J. Demongeot, M. Jelassi, C. Taramasco
ABSTRACT The obesity pandemic is represented by a discrete-time Hopfield Boolean network embedded in continuous-time population dynamics. The influence of the social environment passes through a system of differential equations, whereby obesity spreads by imitation of the most influential neighbors, those who have the highest centrality indices in the network. This property is called “homophily.” Susceptibility and frailty are redefined using network properties. Projections of the spread of obesity are validated on data collected in a French high school.
{"title":"From susceptibility to frailty in social networks: The case of obesity","authors":"J. Demongeot, M. Jelassi, C. Taramasco","doi":"10.1080/08898480.2017.1348718","DOIUrl":"https://doi.org/10.1080/08898480.2017.1348718","url":null,"abstract":"ABSTRACT The obesity pandemic is represented by a discrete-time Hopfield Boolean network embedded in continuous-time population dynamics. The influence of the social environment passes through a system of differential equations, whereby obesity spreads by imitation of the most influential neighbors, those who have the highest centrality indices in the network. This property is called “homophily.” Susceptibility and frailty are redefined using network properties. Projections of the spread of obesity are validated on data collected in a French high school.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"24 1","pages":"219 - 245"},"PeriodicalIF":1.8,"publicationDate":"2017-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2017.1348718","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43966848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-03DOI: 10.1080/08898480.2017.1330017
Noël Bonneuil
{"title":"Sensible Moyen Âge, une histoire des émotions dans l’Occident médiéval [Sensitive Middle Ages, a History of Emotions in the Medieval West], by Damien Bocquet and Piroska Nagy","authors":"Noël Bonneuil","doi":"10.1080/08898480.2017.1330017","DOIUrl":"https://doi.org/10.1080/08898480.2017.1330017","url":null,"abstract":"","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"24 1","pages":"190 - 195"},"PeriodicalIF":1.8,"publicationDate":"2017-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2017.1330017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44803057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-03DOI: 10.1080/08898480.2017.1330013
Pavel Zimmermann
ABSTRACT Several models of old age mortality with time-varying parameters are expressed in a single formula. In these models, the existence of an age threshold above which mortality increases over time and below which mortality decreases over time is problematic. The conditions of appearance of this threshold are expressed and shown on logistic and exponential models with empirical data. The conditions of appearance of the threshold reflect actual situations in developed countries. Richards’ curve avoids the appearance of the threshold with empirical data.
{"title":"Modeling mortality at old age with time-varying parameters","authors":"Pavel Zimmermann","doi":"10.1080/08898480.2017.1330013","DOIUrl":"https://doi.org/10.1080/08898480.2017.1330013","url":null,"abstract":"ABSTRACT Several models of old age mortality with time-varying parameters are expressed in a single formula. In these models, the existence of an age threshold above which mortality increases over time and below which mortality decreases over time is problematic. The conditions of appearance of this threshold are expressed and shown on logistic and exponential models with empirical data. The conditions of appearance of the threshold reflect actual situations in developed countries. Richards’ curve avoids the appearance of the threshold with empirical data.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"24 1","pages":"172 - 180"},"PeriodicalIF":1.8,"publicationDate":"2017-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2017.1330013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49374312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-03DOI: 10.1080/08898480.2017.1330010
S. Molchanov, Joseph Whitmeyer
ABSTRACT A model of population dynamics in continuous time on the lattice contains the Kolmogorov-Petrovski-Piskunov equation as a special case. A limit distribution exists. The first three moments and the correlation function are expressed.
{"title":"Stationary distributions in Kolmogorov-Petrovski- Piskunov-type models with an infinite number of particles","authors":"S. Molchanov, Joseph Whitmeyer","doi":"10.1080/08898480.2017.1330010","DOIUrl":"https://doi.org/10.1080/08898480.2017.1330010","url":null,"abstract":"ABSTRACT A model of population dynamics in continuous time on the lattice contains the Kolmogorov-Petrovski-Piskunov equation as a special case. A limit distribution exists. The first three moments and the correlation function are expressed.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"24 1","pages":"147 - 160"},"PeriodicalIF":1.8,"publicationDate":"2017-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2017.1330010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43046078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-03DOI: 10.1080/08898480.2017.1330014
N. Bonneuil
ABSTRACT The reconstruction of populations by stochastic optimization solves the nontrivial problem of finding demographic flows from population registers or vital statistics and censuses, if available. These flows allow the reconstruction of stocks (age pyramids and vital statistics). After a review of reconstruction methods, the sensitivity analysis shows the robustness of the method by stochastic optimization to flawed or missing values, to the length of the reconstruction period, and to variations in the actual demographic flows.
{"title":"Reconstruction of populations by stochastic optimization: Sensitivity analysis","authors":"N. Bonneuil","doi":"10.1080/08898480.2017.1330014","DOIUrl":"https://doi.org/10.1080/08898480.2017.1330014","url":null,"abstract":"ABSTRACT The reconstruction of populations by stochastic optimization solves the nontrivial problem of finding demographic flows from population registers or vital statistics and censuses, if available. These flows allow the reconstruction of stocks (age pyramids and vital statistics). After a review of reconstruction methods, the sensitivity analysis shows the robustness of the method by stochastic optimization to flawed or missing values, to the length of the reconstruction period, and to variations in the actual demographic flows.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"24 1","pages":"181 - 189"},"PeriodicalIF":1.8,"publicationDate":"2017-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2017.1330014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43945332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-03DOI: 10.1080/08898480.2017.1330012
V. Toepoel, H. Emerson
ABSTRACT Weighting techniques in web surveys based on no probability schemes are devised to correct biases due to self-selection, undercoverage, and nonresponse. In an interactive panel, 38 survey experts addressed weighting techniques and auxiliary variables in web surveys. Most of them corrected all biases jointly and applied calibration and propensity score adjustments. Although they claimed that sociodemographic and web-related variables are the most useful auxiliary variables to employ in adjustments, they considered only sociodemographic variables to correct biases because of their availability.
{"title":"Using experts’ consensus (the Delphi method) to evaluate weighting techniques in web surveys not based on probability schemes","authors":"V. Toepoel, H. Emerson","doi":"10.1080/08898480.2017.1330012","DOIUrl":"https://doi.org/10.1080/08898480.2017.1330012","url":null,"abstract":"ABSTRACT Weighting techniques in web surveys based on no probability schemes are devised to correct biases due to self-selection, undercoverage, and nonresponse. In an interactive panel, 38 survey experts addressed weighting techniques and auxiliary variables in web surveys. Most of them corrected all biases jointly and applied calibration and propensity score adjustments. Although they claimed that sociodemographic and web-related variables are the most useful auxiliary variables to employ in adjustments, they considered only sociodemographic variables to correct biases because of their availability.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"24 1","pages":"161 - 171"},"PeriodicalIF":1.8,"publicationDate":"2017-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2017.1330012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42924807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-23DOI: 10.1080/08898480.2017.1289049
J. Cohen, D. Courgeau
ABSTRACT Taylor’s law states that the variance of the distribution of distance between two randomly chosen individuals is a power function of the mean distance. It applies to the distances between two randomly chosen points in various geometric shapes, subject to a few conditions. In Réunion Island and metropolitan France, at some spatial scales, the empirical frequency distributions of inter-individual distances are predicted accurately by the theoretical frequency distributions of inter-point distances in models of geometric probability under a uniform distribution of points. When these models fail to predict the empirical frequency distributions of inter-individual distances, they provide baselines against which to highlight the spatial distribution of population concentrations.
{"title":"Modeling distances between humans using Taylor’s law and geometric probability","authors":"J. Cohen, D. Courgeau","doi":"10.1080/08898480.2017.1289049","DOIUrl":"https://doi.org/10.1080/08898480.2017.1289049","url":null,"abstract":"ABSTRACT Taylor’s law states that the variance of the distribution of distance between two randomly chosen individuals is a power function of the mean distance. It applies to the distances between two randomly chosen points in various geometric shapes, subject to a few conditions. In Réunion Island and metropolitan France, at some spatial scales, the empirical frequency distributions of inter-individual distances are predicted accurately by the theoretical frequency distributions of inter-point distances in models of geometric probability under a uniform distribution of points. When these models fail to predict the empirical frequency distributions of inter-individual distances, they provide baselines against which to highlight the spatial distribution of population concentrations.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"24 1","pages":"197 - 218"},"PeriodicalIF":1.8,"publicationDate":"2017-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2017.1289049","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49281546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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