On Testing Equality of Means of Correlated Variates with Missing Data on One Response

A statistic is proposed for testing the hypothesis of equality of the means of a bivariate normal distribution with unknown common variance and correlation coefficient when observations are missing on one of the variates. The distribution of the statistic is approximated by a normal distribution under the null hypothesis. The empirical powers of the statistic are computed and compared with those of the conventional paired t and the other known statistics. The power comparisons support the use of the proposed test.     

Combining Cultural Probes and Interviews with Caregivers to Co-Design a Social Mobile Robotic Solution

ObjectivesThe objective of our research is to study the social organization within institutions welcoming dependent older adults and the potential impact of introducing a social robot.Materials and methodsIn a co-design approach with professionals, the observation of behaviors, regulated by social rules and norms, will allow, in a way coherent with our empirical approach, to question the conditions necessary for the design of an acceptable human–robot interaction. The ethnographic observations, which were cancelled due to the Covid crisis, led us to use the “cultural probes” method combined with interviews, to understand the daily work of health professionals better.ResultsThe analysis of the collected data allows us to identify 5 recurrent themes – Time and personnel, the health situation,¹ Communication/Attention, Guiding, Activities – for which we have listed, in this article, the issues encountered, the questions raised and ideas of potential solutions with the use of a social robot.ConclusionThe Cultural Probes approach may seem time-consuming and requires a significant investment, but it has allowed us to maintain regular contact during the pandemic. In addition, the qualitative data collected proved to be a good discussion tool.     

Quantile regression for doubly censored data

Double censoring often occurs in registry studies when left censoring is present in addition to right censoring. In this work, we propose a new analysis strategy for such doubly censored data by adopting a quantile regression model. We develop computationally simple estimation and inference procedures by appropriately using the embedded martingale structure. Asymptotic properties, including the uniform consistency and weak convergence, are established for the resulting estimators. Moreover, we propose conditional inference to address the special identifiability issues attached to the double censoring setting. We further show that the proposed method can be readily adapted to handle left truncation. Simulation studies demonstrate good finite-sample performance of the new inferential procedures. The practical utility of our method is illustrated by an analysis of the onset of the most commonly investigated respiratory infection, Pseudomonas aeruginosa, in children with cystic fibrosis through the use of the U.S. Cystic Fibrosis Registry.     

Improved variance estimators for one- and two-parameter models of nucleotide substitution

The current variance estimators for Jukes and Cantor's one-parameter model and Kimura's two-parameter model tend to underestimate the true variances when the true proportion of differences between the two sequences under study is not small. In this paper, we developed improved variance estimators, using a higher-order Taylor expansion and empirical methods. The new estimators outperform the conventional estimators and provide accurate estimates of the true variances.     

Estimating the number of species in a stochastic abundance model

Consider a stochastic abundance model in which the species arrive in the sample according to independent Poisson processes, where the abundance parameters of the processes follow a gamma distribution. We propose a new estimator of the number of species for this model. The estimator takes the form of the number of duplicated species (i.e., species represented by two or more individuals) divided by an estimated duplication fraction. The duplication fraction is estimated from all frequencies including singleton information. The new estimator is closely related to the sample coverage estimator presented by Chao and Lee (1992, Journal of the American Statistical Association 87, 210-217). We illustrate the procedure using the Malayan butterfly data discussed by Fisher, Corbet, and Williams (1943, Journal of Animal Ecology 12, 42-58) and a 1989 Christmas Bird Count dataset collected in Florida, U.S.A. Simulation studies show that this estimator compares well with maximum likelihood estimators (i.e., empirical Bayes estimators from the Bayesian viewpoint) for which an iterative numerical procedure is needed and may be infeasible.     

基于EMD的河北省粮食产量波动的结构特征及其成因的分析

在分析河北省粮食产量变化的时间序列总体特征的基础之上,对河北粮食产量波动结构特征及其成因进行研究,旨在为指导河北省粮食安全生产提供科学的理论依据.综合运用EMD法、剩余法和方差分析法,对河北粮食产量波动结构特征及其成因进行研究.结果表明:在品种上,小麦和玉米两大主要粮食作物产量比重呈现递增趋势,两者之和达到了89.91%,其变动对粮食总产的变动起着举足轻重的作用;杂粮作物和稻谷所占比例较小,且呈逐年缩减趋势;小麦、玉米产量波动的方差贡献率分别为64.36%和31.72%,是河北省粮食总产波动的第一和第二主控作物;稻谷和杂粮作物由于其粮食产量基数较小对河北粮食总产波动的影响较小.在空间上,河北省粮食产量的波动值分布在0～0.35之间的地区比例约为90%,表明其强度主要处于中等水平;燕山太行山山前平原区和冀鲁豫低洼平原区粮食产量波动的方差贡献率分别为22.05%和17.82%,是河北省粮食总产波动的第一和第二主控区;辽吉西蒙东南冀北山地和后山坝上高原区的粮食产量波动对河北省粮食总产波动影响较小.研究表明综合运用EMD法、剩余法和方差分析法,对河北粮食产量波动结构特征及其成因进行研究是可行的.利用这种综合方法,提高了单独使用一种方法进行波动性分析的精度,为分析波动问题提供了新的科学的理论和方法.