Improving the detection of unusual observations in high‐dimensional settings

Multivariate control charts are used to monitor stochastic processes for changes and unusual observations. Hotelling's T² statistic is calculated for each new observation and an out‐of‐control signal is issued if it goes beyond the control limits. However, this classical approach becomes unreliable as the number of variables p approaches the number of observations n, and impossible when p exceeds n. In this paper, we devise an improvement to the monitoring procedure in high‐dimensional settings. We regularise the covariance matrix to estimate the baseline parameter and incorporate a leave‐one‐out re‐sampling approach to estimate the empirical distribution of future observations. An extensive simulation study demonstrates that the new method outperforms the classical Hotelling T² approach in power, and maintains appropriate false positive rates. We demonstrate the utility of the method using a set of quality control samples collected to monitor a gas chromatography–mass spectrometry apparatus over a period of 67 days.     

旅游景点公示语英译现状调查与分析——以镇江市6家公园为例

公示语是一种具有感召力的文本,意在促使读者按照文本预期意图做出反应;旅游景点公示语是景点管理机构与游客对话的重要手段和渠道。镇江是江苏省重点旅游城市之一,景点公共标识都会使用英语译文。选取镇江市6家公园的公示语英译为个案,通过实地采集大量语料对旅游景点公示语英译的现状进行调查,分析产生错误的原因并提出相应的改进建议。     

多媒体案例教学在市场营销学教学中的应用

从科学分组、具体应用、如何合理评价学生三方面进行研究突破,提出与以往完全不同的多媒体案例教学模式。这种方法不仅能使学生充分掌握市场营销理论知识,而且对目前很多高校应用型人才的培养起到了非常重要的作用。     

Characteristics of Couples Who Attend Family Services Counselor Visits in Relationship Education

Case management services for low-income couples receiving relationship education have been required by federal funding agencies. Studies examining relationship education outcomes for low-income couples have yet to address participant characteristics of those who attend case management services (e.g., distressed vs. nondistressed). Thus, this study examined the influence of baseline relationship satisfaction and demographics on attendance at case management visits for 2,628 low-income, partnered participants who attended relationship education. Findings indicated that participants who reported higher baseline relationship distress attended more family services counselor (FSC) visits. However, when we added demographics to the model, relationship distress no longer predicted FSC visits, whereas income served as a predictor for men and women, with those reporting greater monthly income attending more FSC visits.     

Family engagement within the context of assessment in child protection practice: The case of Estonia

Engagement in the context of child protection is of significant international interest, as the participation of family is a central notion in child and family social work. Drawing on in‐depth, semistructured interviews with a sample of 26 child protection workers in 1 region in Estonia, this article reports the findings of the participants' perspectives on family engagement in the context of child protection assessment. Child protection workers perceive the engagement related to 3 aspects: first, it is associated to the acts of the worker; second, it is associated to parental part of actions—depending on parents themselves; and third, engagement was seen as “doing together” with the family, referring to partnership. The aim of the engagement was mainly considered in the terms of empowerment—empowering family to cope on their own and to take charge of their lives. The negative image of child protection was recognised as one of the main barriers to the family engagement. Understanding the family and their situation was seen as the basis for a trusting relationship, being the most crucial factor to promoting family engagement.     

Approximate confidence intervals for the weighted kappa coefficient of a binary diagnostic test subject to a case–control design

Case–control design to assess the accuracy of a binary diagnostic test (BDT) is very frequent in clinical practice. This design consists of applying the diagnostic test to all of the individuals in a sample of those who have the disease and in another sample of those who do not have the disease. The sensitivity of the diagnostic test is estimated from the case sample and the specificity is estimated from the control sample. Another parameter which is used to assess the performance of a BDT is the weighted kappa coefficient. The weighted kappa coefficient depends on the sensitivity and specificity of the diagnostic test, on the disease prevalence and on the weighting index. In this article, confidence intervals are studied for the weighted kappa coefficient subject to a case–control design and a method is proposed to calculate the sample sizes to estimate this parameter. The results obtained were applied to a real example.     

FDR control of detected regions by multiscale matched filtering

Feature extraction from observed noisy samples is a common important problem in statistics and engineering. This paper presents a novel general statistical approach to the region detection problem in long data sequences. The proposed technique is a multiscale kernel regression in conjunction with statistical multiple testing for region detection while controlling the false discovery rate (FDR) and maximizing the signal-to-noise ratio via matched filtering. This is achieved by considering a one-dimensional region detection problem as its equivalent zero-dimensional peak detection problem. The detection method does not require a priori knowledge of the shape of the nonzero regions. However, if the shape of the nonzero regions is known a priori, e.g., rectangular pulse, the signal regions can also be reconstructed from the detected peaks, seen as their topological point representatives. Simulations show that the method can effectively perform signal detection and reconstruction in the simulated data under high noise conditions, while controlling the FDR of detected regions and their reconstructed length.     

On robustness of the Shiryaev–Roberts change-point detection procedure under parameter misspecification in the post-change distribution

The gist of the quickest change-point detection problem is to detect the presence of a change in the statistical behavior of a series of sequentially made observations, and do so in an optimal detection-speed-versus-“false-positive”-risk manner. When optimality is understood either in the generalized Bayesian sense or as defined in Shiryaev's multi-cyclic setup, the so-called Shiryaev–Roberts (SR) detection procedure is known to be the “best one can do”, provided, however, that the observations’ pre- and post-change distributions are both fully specified. We consider a more realistic setup, viz. one where the post-change distribution is assumed known only up to a parameter, so that the latter may be misspecified. The question of interest is the sensitivity (or robustness) of the otherwise “best” SR procedure with respect to a possible misspecification of the post-change distribution parameter. To answer this question, we provide a case study where, in a specific Gaussian scenario, we allow the SR procedure to be “out of tune” in the way of the post-change distribution parameter, and numerically assess the effect of the “mistuning” on Shiryaev's (multi-cyclic) Stationary Average Detection Delay delivered by the SR procedure. The comprehensive quantitative robustness characterization of the SR procedure obtained in the study can be used to develop the respective theory as well as to provide a rational for practical design of the SR procedure. The overall qualitative conclusion of the study is an expected one: the SR procedure is less (more) robust for less (more) contrast changes and for lower (higher) levels of the false alarm risk.     

Retrospective change detection in categorical time series

The aim of this paper is to propose methods of detecting change in the coefficients of a multinomial logistic regression model for categorical time series offline. The alternatives to the null hypothesis of stationarity can be either the hypothesis that it is not true, or that there is a temporary change in the sequence. We use the efficient score vector of the partial likelihood function. This has several advantages. First, the alternative value of the parameter does not have to be estimated; hence, we have a procedure that has a simple structure with only one parameter estimation using all available observations. This is in contrast with the generalized likelihood ratio-based change point tests. The efficient score vector is used in various ways. As a vector, its components correspond to the different components of the multinomial logistic regression model’s parameter vector. Using its quadratic form a test can be defined, where the presence of a change in any or all parameters is tested for. If there are too many parameters one can test for any subset while treating the rest as nuisance parameters. Our motivating example is a DNA sequence of four categories, and our test result shows that in the published data the distribution of the four categories is not stationary.