{"title":"Dependent radius marks of Laguerre tessellations: a case study","authors":"Dietrich Stoyan, Viktor Beneš, Filip Seitl","doi":"10.1111/anzs.12314","DOIUrl":"10.1111/anzs.12314","url":null,"abstract":"<div>\u0000 \u0000 <p>We study a particular marked three-dimensional point process sample that represents a Laguerre tessellation. It comes from a polycrystalline sample of aluminium alloy material. The ‘points’ are the cell generators while the ‘marks’ are radius marks that control the size and shape of the tessellation cells. Our statistical mark correlation analyses show that the marks of the sample are in clear and plausible spatial correlation: the marks of generators close together tend to be small and similar and the form of the correlation functions does not justify geostatistical marking. We show that a simplified modelling of tessellations by Laguerre tessellations with independent radius marks may lead to wrong results. When we started from the aluminium alloy data and generated random marks by random permutation we obtained tessellations with characteristics quite different from the original ones. We observed similar behaviour for simulated Laguerre tessellations. This fact, which seems to be natural for the given data type, makes fitting of models to empirical Laguerre tessellations quite difficult: the generator points and radius marks have to be modelled simultaneously. This may imply that the reconstruction methods are more efficient than point-process modelling if only samples of similar Laguerre tessellations are needed. We also found that literature recipes for bandwidth choice for estimating correlation functions should be used with care.</p>\u0000 </div>","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"63 1","pages":"19-32"},"PeriodicalIF":1.1,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/anzs.12314","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80348739","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}
A. P. Verbyla, J. De Faveri, D. M. Deery, G. J. Rebetzke
{"title":"Modelling temporal genetic and spatio-temporal residual effects for high-throughput phenotyping data*","authors":"A. P. Verbyla, J. De Faveri, D. M. Deery, G. J. Rebetzke","doi":"10.1111/anzs.12336","DOIUrl":"10.1111/anzs.12336","url":null,"abstract":"<div>\u0000 \u0000 <p>High-throughput phenomics data are being collected in both the laboratory and the field. The data are often collected at many time points and there may be spatial variation in the laboratory or field that impacts on the growth of the plants, and that may influence the traits of interest. Modelling the genetic effects is of primary interest in such studies, but these effects might be biased if non-genetic effects present in the experiment are ignored. With data that are collected both in time and space, there may be a need to jointly model these multi-dimensional non-genetic effects. Thus both modelling of genetic effects over time and non-genetic effects over time and space in a one-stage analysis is considered. An experiment that involves field phenomics data with four dimensions, two in space and two in time, provides the vehicle to examine the models. Factor analytic (FA) models are often used for genetic effects for different environments to provide reliable estimates of genetic variances and correlations. As the time dimension defines the environments, FA models are examined for the phenomics data. Reduced rank tensor smoothing splines are presented as a possible approach for modelling the spatio-temporal effects, although an additional term is included for heterogeneity over the two time dimensions. This approach is feasible, although very time-consuming. The process of model selection for the genetic effects is presented including tests, information criteria and diagnostics. Comparisons of more simplistic models are made with the reduced rank tensor spline. This also shows the interplay between the genetic and residual models in model selection.</p>\u0000 </div>","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"63 2","pages":"284-308"},"PeriodicalIF":1.1,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/anzs.12336","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89156281","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":"Conditional intensity: A powerful tool for modelling and analysing point process data","authors":"Peter J. Diggle","doi":"10.1111/anzs.12331","DOIUrl":"10.1111/anzs.12331","url":null,"abstract":"<div>\u0000 \u0000 <p>The conditional intensity function of a spatial point process describes how the probability that a point of the process occurs ‘at’ a particular point in its carrier space depends on the realisation of the process in the remainder of the carrier space. Provided that the point process is simple, the conditional intensity determines all of the properties of the process, in particular its likelihood function. In this paper, we review the use of the conditional intensity function in the formulation of point process models and in making inferences from point process data, giving separate consideration to temporal, spatial and spatiotemporal settings. We argue that the conditional intensity function should take centre-stage in spatiotemporal point process modelling and analysis.</p>\u0000 </div>","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"63 1","pages":"83-92"},"PeriodicalIF":1.1,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/anzs.12331","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86952633","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":"Non-parametric depth-based tests for the multivariate location problem","authors":"Sakineh Dehghan, Mohammad Reza Faridrohani","doi":"10.1111/anzs.12328","DOIUrl":"10.1111/anzs.12328","url":null,"abstract":"<div>\u0000 \u0000 <p>In this paper, using the notion of data depth, we describe two classes of affine invariant test statistics for the one-sample location problem. The tests are implemented through the idea of permutation tests. The performance of the test against some competitors is investigated with an extensive simulation study. It is observed that the tests perform well when compared to their competitors for a wide spectrum of alternatives. If the proposed test is defined based on a moment-free depth function, then it is not inherently required to have finite moments of any order and the tests have broader applicability than some of the existing tests. The robustness property of the proposed tests is considered with a simulation study. Finally, we apply the tests to a real data example.</p>\u0000 </div>","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"63 2","pages":"309-330"},"PeriodicalIF":1.1,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/anzs.12328","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80013153","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":"New moderation methods of higher school certificate assessments: a case study of the New South Wales practice","authors":"Yanlin Shi","doi":"10.1111/anzs.12317","DOIUrl":"10.1111/anzs.12317","url":null,"abstract":"<div>\u0000 \u0000 <p>The Higher School Certificate (HSC) is the credential awarded to secondary school students in New South Wales (NSW), Australia. This paper reviews the current moderation process of the HSC and introduces and compares a range of modern statistical methods. With a comprehensive analysis of the complete 2013–2016 HSC results, we show that the monotone spline regression with the Huber loss function consistently beats the existing moderation method. With its simple structure, fast execution and improved effectiveness, this new moderation model is an ideal replacement of the in-force quadratic for the HSC practice in NSW.</p>\u0000 </div>","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"63 2","pages":"257-283"},"PeriodicalIF":1.1,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/anzs.12317","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87803813","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":"Forecasting the old-age dependency ratio to determine a sustainable pension age","authors":"Rob J. Hyndman, Yijun Zeng, Han Lin Shang","doi":"10.1111/anzs.12330","DOIUrl":"10.1111/anzs.12330","url":null,"abstract":"<div>\u0000 \u0000 <p>We forecast the old-age dependency ratio for Australia under various pension age proposals, and estimate a pension age scheme that will provide a stable old-age dependency ratio at a specified level. Our approach involves a stochastic population forecasting method based on coherent functional data models for mortality, fertility and net migration, which we use to simulate the future age-structure of the population. Our results suggest that the Australian pension age should be increased to 68 by 2030, 69 by 2036 and 70 by 2050, in order to maintain the old-age dependency ratio at 23%, just above the 2018 level. Our general approach can easily be extended to other target levels of the old-age dependency ratio and to other countries.</p>\u0000 </div>","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"63 2","pages":"241-256"},"PeriodicalIF":1.1,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/anzs.12330","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77019366","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 shared parameter mixture model for longitudinal income data with missing responses and zero rounding","authors":"Francis K.C. Hui, Howard D. Bondell","doi":"10.1111/anzs.12323","DOIUrl":"10.1111/anzs.12323","url":null,"abstract":"The analysis of longitudinal income data is often made challenging for several reasons. For example, in a national Australian survey on income over time, a non‐negligible proportion of responses are missing, and it is believed the missingness mechanism is non‐ignorable. Also, there are a large number of reported zero incomes, some of which may be true zeros (corresponding to individuals who legitimately do not earn an income), while some may be false zeros (corresponding to individuals choosing to round their income to zero). We propose a new shared parameter mixture (SPM) model for analysing semi‐continuous longitudinal income data, which addresses the two challenges of income non‐response and zero rounding. This is accomplished by jointly modelling an individual's underlying income together with the probability of missingness and rounding to zero, where both probabilities are permitted to vary in a smooth manner with their underlying non‐zero income. Applying the SPM model to the Australian income survey reveals that on average, older female individuals and individuals with a long‐term health condition are considerably less likely to earn an income, while income tended to be highest for male individuals on fixed‐term/permanent job contracts between ages 50 and 60. Furthermore there is evidence of both zero rounding, and conditional on the assumed missingness mechanism, individuals with incomes at the higher and lower ends are more likely to not report their income.","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"63 2","pages":"221-240"},"PeriodicalIF":1.1,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/anzs.12323","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89592499","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":"Adversarial risk analysis for first-price sealed-bid auctions","authors":"Muhammad Ejaz, Chaitanya Joshi, Stephen Joe","doi":"10.1111/anzs.12315","DOIUrl":"10.1111/anzs.12315","url":null,"abstract":"<div>\u0000 \u0000 <p>Adversarial risk analysis (ARA) is an upcoming methodology that is considered to have advantages over the traditional decision-theoretic and game-theoretic approaches. ARA solutions for first-price sealed-bid (FPSB) auctions have been found but only under strong assumptions which make the model somewhat unrealistic. In this paper, we use ARA methodology to model FPSB auctions using more realistic assumptions. We define a new utility function that considers bidders’ wealth, we assume a reserve price and find solutions not only for risk-neutral but also for risk-averse as well as risk-seeking bidders. We model the problem using ARA for non-strategic play and level-<i>k</i> thinking solution concepts.</p>\u0000 </div>","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"63 2","pages":"357-376"},"PeriodicalIF":1.1,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/anzs.12315","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75026347","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":"On distance based goodness of fit tests for missing data when missing occurs at random","authors":"Subhra Sankar Dhar, Ujjwal Das","doi":"10.1111/anzs.12313","DOIUrl":"10.1111/anzs.12313","url":null,"abstract":"<div>\u0000 \u0000 <p>Various non-parametric goodness of fit tests have already been investigated in the literature. However, those tests are rarely used in the case of missing observations. We here study the goodness of fit test for missing data based on <i>L</i><sub><i>p</i></sub> distances along with Kolmogorov–Smirnov and Cramer–von-Mises distances when missingness occurs at random. The asymptotic distributions of the proposed test statistics have been derived under contiguous alternatives that enable us to investigate the asymptotic local power of the tests. We also study the performance of the tests for finite samples using simulation, and the tests perform well for those cases. The usefulness of the tests is illustrated on three real data sets.</p>\u0000 </div>","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"63 2","pages":"331-356"},"PeriodicalIF":1.1,"publicationDate":"2021-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/anzs.12313","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81486366","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":"Bayesian decision rules to classification problems","authors":"Yuqi Long, Xingzhong Xu","doi":"10.1111/anzs.12325","DOIUrl":"10.1111/anzs.12325","url":null,"abstract":"<div>\u0000 \u0000 <p>In this paper, we analysed classification rules under Bayesian decision theory. The setup we considered here is fairly general, which can represent all possible parametric models. The Bayes classification rule we investigated minimises the Bayes risk under general loss functions. Among the existing literatures, the 0-1 loss function appears most frequently, under which the Bayes classification rule is determined by the posterior predictive densities. Theoretically, we extended the Bernstein–von Mises theorem to the multiple-sample case. On this basis, the oracle property of Bayes classification rule has been discussed in detail, which refers to the convergence of the Bayes classification rule to the one built from the true distributions, as the sample size tends to infinity. Simulations show that the Bayes classification rules do have some advantages over the traditional classifiers, especially when the number of features approaches the sample size.</p>\u0000 </div>","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"63 2","pages":"394-415"},"PeriodicalIF":1.1,"publicationDate":"2021-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/anzs.12325","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89269715","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}