Journal of the Royal Statistical Society Series C-Applied Statistics最新文献

{"title":"Network Hawkes process models for exploring latent hierarchy in social animal interactions","authors":"Owen G. Ward,&nbsp;Jing Wu,&nbsp;Tian Zheng,&nbsp;Anna L. Smith,&nbsp;James P. Curley","doi":"10.1111/rssc.12581","DOIUrl":"10.1111/rssc.12581","url":null,"abstract":"<p>Group-based social dominance hierarchies are of essential interest in understanding social structure (DeDeo &amp; Hobson in, Proceedings of the National Academy of Sciences 118(21), 2021). Recent animal behaviour research studies can record aggressive interactions observed over time. Models that can explore the underlying hierarchy from the observed temporal dynamics in behaviours are therefore crucial. Traditional ranking methods aggregate interactions across time into win/loss counts, equalizing dynamic interactions with the underlying hierarchy. Although these models have gleaned important behavioural insights from such data, they are limited in addressing many important questions that remain unresolved. In this paper, we take advantage of the observed interactions' timestamps, proposing a series of network point process models with latent ranks. We carefully design these models to incorporate important theories on animal behaviour that account for dynamic patterns observed in the interaction data, including the winner effect, bursting and pair-flip phenomena. Through iteratively constructing and evaluating these models we arrive at the final cohort Markov-modulated Hawkes process (C-MMHP), which best characterizes all aforementioned patterns observed in interaction data. As such, inference on our model components can be readily interpreted in terms of theories on animal behaviours. The probabilistic nature of our model allows us to estimate the uncertainty in our ranking. In particular, our model is able to provide insights into the distribution of power within the hierarchy which forms and the strength of the established hierarchy. We compare all models using simulated and real data. Using statistically developed diagnostic perspectives, we demonstrate that the C-MMHP model outperforms other methods, capturing relevant latent ranking structures that lead to meaningful predictions for real data.</p>","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82071302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust correspondence analysis","authors":"Marco Riani,&nbsp;Anthony C. Atkinson,&nbsp;Francesca Torti,&nbsp;Aldo Corbellini","doi":"10.1111/rssc.12580","DOIUrl":"10.1111/rssc.12580","url":null,"abstract":"<p>Correspondence analysis is a method for the visual display of information from two-way contingency tables. We introduce a robust form of correspondence analysis based on minimum covariance determinant estimation. This leads to the systematic deletion of outlying rows of the table and to plots of greatly increased informativeness. Our examples are trade flows of clothes and consumer evaluations of the perceived properties of cars. The robust method requires that a specified proportion of the data be used in fitting. To accommodate this requirement we provide an algorithm that uses a subset of complete rows and one row partially, both sets of rows being chosen robustly. We prove the convergence of this algorithm.</p>","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rss.onlinelibrary.wiley.com/doi/epdf/10.1111/rssc.12580","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82808130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal ETAS model with a renewal main-shock arrival process","authors":"Tom Stindl,&nbsp;Feng Chen","doi":"10.1111/rssc.12579","DOIUrl":"10.1111/rssc.12579","url":null,"abstract":"<p>We propose a spatiotemporal point process model that enhances the classical Epidemic-Type Aftershock Sequence (ETAS) model. This is achieved with the introduction of a renewal main-shock arrival process and we call this extension the renewal ETAS (RETAS) model. This modification is similar in spirit to the renewal Hawkes (RHawkes) process but the conditional intensity process supports a spatial component. It empowers the main-shock intensity to reset upon the arrival of main-shocks. This allows for heavier clustering of main-shocks than the classical spatiotemporal ETAS model. We introduce a likelihood evaluation algorithm for parameter estimation and provide a novel procedure to evaluate the fitted model's goodness-of-fit (GOF) based on a sequential application of the Rosenblatt transformation. A simulation algorithm for the RETAS model is outlined and used to validate the numerical performance of the likelihood evaluation algorithm and GOF test procedure. We illustrate the proposed model and methods on various earthquake catalogues around the world each with distinctly different seismic activity. These catalogues demonstrate the RETAS model's additional flexibility in comparison to the classical spatiotemporal ETAS model and emphasizes the potential for superior modelling and forecasting of seismicity.</p>","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rss.onlinelibrary.wiley.com/doi/epdf/10.1111/rssc.12579","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79644802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Specification analysis for technology use and teenager well-being: Statistical validity and a Bayesian proposal","authors":"Christoph Semken,&nbsp;David Rossell","doi":"10.1111/rssc.12578","DOIUrl":"10.1111/rssc.12578","url":null,"abstract":"A key issue in science is assessing robustness to data analysis choices, while avoiding selective reporting and providing valid inference. Specification Curve Analysis is a tool intended to prevent selective reporting. Alas, when used for inference it can create severe biases and false positives, due to wrongly adjusting for covariates, and mask important treatment effect heterogeneity. As our motivating application, it led an influential study to conclude there is no relevant association between technology use and teenager mental well‐being. We discuss these issues and propose a strategy for valid inference. Bayesian Specification Curve Analysis (BSCA) uses Bayesian Model Averaging to incorporate covariates and heterogeneous effects across treatments, outcomes and subpopulations. BSCA gives significantly different insights into teenager well‐being, revealing that the association with technology differs by device, gender and who assesses well‐being (teenagers or their parents).","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rss.onlinelibrary.wiley.com/doi/epdf/10.1111/rssc.12578","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83476610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Missing data patterns in runners’ careers: do they matter?","authors":"M. Stival, M. Bernardi, Manuela Cattelan, P. Dellaportas","doi":"10.1093/jrsssc/qlad009","DOIUrl":"https://doi.org/10.1093/jrsssc/qlad009","url":null,"abstract":"\u0000 Predicting the future performance of young runners is an important research issue in experimental sports science and performance analysis. We analyse a dataset with annual seasonal best performances of male middle distance runners for a period of 14 years and provide a modelling framework that accounts for both the fact that each runner has typically run in 3 distance events (800, 1,500, and 5,000 m) and the presence of periods of no running activities. We propose a latent class matrix-variate state space model and we empirically demonstrate that accounting for missing data patterns in runners’ careers improves the out of sample prediction of their performances over time. In particular, we demonstrate that for this analysis, the missing data patterns provide valuable information for the prediction of runner’s performance.","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80455942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heterogeneous graphical model for non-negative and non-Gaussian \u0000 \u0000 \u0000 PM\u0000 2.5\u0000 \u0000 data","authors":"Jiaqi Zhang,&nbsp;Xinyan Fan,&nbsp;Yang Li,&nbsp;Shuangge Ma","doi":"10.1111/rssc.12575","DOIUrl":"10.1111/rssc.12575","url":null,"abstract":"<p>Studies on the conditional relationships between \u0000<math>\u0000 <mrow>\u0000 <msub>\u0000 <mtext>PM</mtext>\u0000 <mn>2.5</mn>\u0000 </msub>\u0000 </mrow></math> concentrations among different regions are of great interest for the joint prevention and control of air pollution. Because of seasonal changes in atmospheric conditions, spatial patterns of \u0000<math>\u0000 <mrow>\u0000 <msub>\u0000 <mtext>PM</mtext>\u0000 <mn>2.5</mn>\u0000 </msub>\u0000 </mrow></math> may differ throughout the year. Additionally, concentration data are both non-negative and non-Gaussian. These data features pose significant challenges to existing methods. This study proposes a heterogeneous graphical model for non-negative and non-Gaussian data via the score matching loss. The proposed method simultaneously clusters multiple datasets and estimates a graph for variables with complex properties in each cluster. Furthermore, our model involves a network that indicate similarity among datasets, and this network can have additional applications. In simulation studies, the proposed method outperforms competing alternatives in both clustering and edge identification. We also analyse the \u0000<math>\u0000 <mrow>\u0000 <msub>\u0000 <mtext>PM</mtext>\u0000 <mn>2.5</mn>\u0000 </msub>\u0000 </mrow></math> concentrations' spatial correlations in Taiwan's regions using data obtained in year 2019 from 67 air-quality monitoring stations. The 12 months are clustered into four groups: January–March, April, May–September and October–December, and the corresponding graphs have 153, 57, 86 and 167 edges respectively. The results show obvious seasonality, which is consistent with the meteorological literature. Geographically, the \u0000<math>\u0000 <mrow>\u0000 <msub>\u0000 <mtext>PM</mtext>\u0000 <mn>2.5</mn>\u0000 </msub>\u0000 </mrow></math> concentrations of north and south Taiwan regions correlate more respectively. These results can provide valuable information for developing joint air-quality control strategies.</p>","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82229817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Bayesian spatio-temporal analysis of markets during the Finnish 1860s famine","authors":"Tiia-Maria Pasanen,&nbsp;Miikka Voutilainen,&nbsp;Jouni Helske,&nbsp;Harri Högmander","doi":"10.1111/rssc.12577","DOIUrl":"10.1111/rssc.12577","url":null,"abstract":"<p>We develop a Bayesian spatio-temporal model to study pre-industrial grain market integration during the Finnish famine of the 1860s. Our model takes into account several problematic features often present when analysing multiple spatially interdependent time series. For example, compared with the error correction methodology commonly applied in econometrics, our approach allows simultaneous modelling of multiple interdependent time series avoiding cumbersome statistical testing needed to predetermine the market leader as a point of reference. Furthermore, introducing a flexible spatio-temporal structure enables analysing detailed regional and temporal dynamics of the market mechanisms. Applying the proposed method, we detected spatially asymmetric ‘price ripples’ that spread out from the shock origin. We corroborated the existing literature on the speedier adjustment to emerging price differentials during the famine, but we observed this principally in urban markets. This hastened return to long-run equilibrium means faster and longer travel of price shocks, implying prolonged out-of-equilibrium dynamics, proliferated influence of market shocks, and, importantly, a wider spread of famine conditions.</p>","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rss.onlinelibrary.wiley.com/doi/epdf/10.1111/rssc.12577","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81122126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nowcasting COVID-19 deaths in England by age and region","authors":"Shaun R. Seaman,&nbsp;Pantelis Samartsidis,&nbsp;Meaghan Kall,&nbsp;Daniela De Angelis","doi":"10.1111/rssc.12576","DOIUrl":"10.1111/rssc.12576","url":null,"abstract":"<p>Understanding the trajectory of the daily number of COVID-19 deaths is essential to decisions on how to respond to the pandemic, but estimating this trajectory is complicated by the delay between deaths occurring and being reported. In England the delay is typically several days, but it can be weeks. This causes considerable uncertainty about how many deaths occurred in recent days. Here we estimate the deaths per day in five age strata within seven English regions, using a Bayesian model that accounts for reporting-day effects and longer-term changes in the delay distribution. We show how the model can be computationally efficiently fitted when the delay distribution is the same in multiple strata, for example, over a wide range of ages.</p>","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9349735/pdf/RSSC-9999-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10255246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unconventional policies effects on stock market volatility: The MAP approach","authors":"Demetrio Lacava,&nbsp;Giampiero M. Gallo,&nbsp;Edoardo Otranto","doi":"10.1111/rssc.12574","DOIUrl":"10.1111/rssc.12574","url":null,"abstract":"<p>Taking the European Central Bank unconventional policies as a reference, we suggest a class of multiplicative error models (MEMs) tailored to analyse the impact such policies have on stock market volatility. The new set of models, called MEM with asymmetry and policy effects, keeps the base volatility dynamics separate from a component reproducing policy effects, with an increase in volatility on announcement days and a decrease unfolding implementation effects. When applied to four Eurozone markets, a model confidence set approach finds a significant improvement of the forecasting power of the proxy after the expanded asset purchase programme implementation. A multi-step ahead forecasting exercise estimates the duration of the effect; by shocking the policy variable, we are able to quantify the reduction in volatility which is more marked for debt-troubled countries.</p>","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rss.onlinelibrary.wiley.com/doi/epdf/10.1111/rssc.12574","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72429158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multilevel network item response modelling for discovering differences between innovation and regular school systems in Korea","authors":"Ick Hoon Jin,&nbsp;Minjeong Jeon,&nbsp;Michael Schweinberger,&nbsp;Jonghyun Yun,&nbsp;Lizhen Lin","doi":"10.1111/rssc.12569","DOIUrl":"10.1111/rssc.12569","url":null,"abstract":"<p>The innovation school system in South Korea has been developed in response to the traditional high-pressure school system in South Korea, with a view to cultivate a bottom-up and student-centred educational culture. Despite its ambitious goals, questions have been raised about the success of the innovation school system. Leveraging data from the Gyeonggi Education Panel Study along with advances in the statistical analysis of network data and educational data, we compare the two school systems in more depth. We find that some schools are indeed different from others, and those differences are not detected by conventional multilevel models. Having said that, we do not find much evidence that the innovation school system differs from the regular school system in terms of self-reported mental well-being, although we do detect differences among some schools that appear to be unrelated to the school system.</p>","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2022-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82591960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}