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We enjoyed reading Professor Efron's (Brad) paper just as much as we enjoyed listening to his June 2019 lecture in Leiden. Interestingly, Efron puts the pure predictive algorithms to the test in a scenario where the sample size is extremely moderate by today's standards ( I n i = 102). In the knockoff framework, one can use I any i black-box (any predictive model) to identify any kind possible association - linear or not - between a large set of explanatory variables HT ht and an outcome I Y i . This framework rigorously tests whether the conditional distribution HT ht actually depends on any of the variables I X SB j sb i without assuming any model for how I X i and I Y i are connected (Candès et al. 2018). [Extracted from the article]

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The author discusses papers on synthetic data published in the previous issue of the journal. Topics covered include the common themes identified in the papers which deal with synthetic data according to the definition commonly used in the statistical disclosure control community, a different approach for data protection based on noise infusion discussed in one synthetic data paper, and a discussion on data dissemination.

This paper aims to help students better grasp the required professional knowledge and core concepts. This paper presents a design method for a multi-layer knowledge base based on XML. According to learners' identity characteristics and learning behaviour, using the mathematical statistics method, the feature expression for the learning system is constructed. Multivariable linear regression theory establishes convergence constraints for accurate and deep mining. The average detection results of the collected samples are used for high-quality deep mining of user portraits in the learning system. This project intends to study the method of solving accurate confidence intervals for user portrait data in the education system. Excel and Access are used to complete the data collection of the teaching object and the construction of the database. A multi-mode interactive editing and processing method of user portrait information for education systems is studied in cloud computing. Finally, a learning system based on mathematical loading mode is proposed, and an object-oriented learning recommendation system is designed. The developed teaching software can enable students to get more teaching guidance when they acquire the required knowledge to improve students' learning effect effectively. [ABSTRACT FROM AUTHOR]

Note, for instance, that the probabilities given by Castellares et al. ([1]) in page 4 are the same than those shown in expression (9.115) in the book by Johnson et al. ([3]), with the change of parameters Graph HT ht and Graph HT ht Neyman type A (NTA) distribution is frequently used in Biology, Biodosimetry, Environmental Sciences, Epidemiology, etc. A count random variable I X i is said to follow a stopped-sum Poisson, compound Poisson, multiple Poisson or clustered-Poisson distribution, if it can be represented as Graph HT ht where I N i is a Poisson random variable with parameter Graph HT ht and Graph HT ht are independent, identically distributed random variables that are also independent of I N i . [Extracted from the article]

The 2022 International Symposium on Nonparametric Statistics was held in Paphos, Cyprus and co-sponsored by the Institute of Mathematical Statistics and the Bernoulli Society of Mathematical Statistics and Probability. The symposium brought together researchers from around the world to discuss recent advances and trends in nonparametric statistics. The conference covered a wide range of topics, including nonparametric estimation, hypothesis testing, adaptive inference, high-dimensional statistical inference, and more. The special issue of the Journal of Nonparametric Statistics contains papers that have undergone a peer review process and cover diverse areas of nonparametric statistics. [Extracted from the article]

In this paper some issues relative to the gap between the traditional theory of control charts and real problems practitioners encounter are discussed. We consider both the general reasons for this discrepancy and different examples of misunderstandings. The trend to develop statistics as mathematical branch of science in the area of statistical process control has led to (i) ignoring many real complexities; (ii) creating many new types of charts that rarely help practitioners to improve their processes. We offer some practical advices, such as the introduction of two types of the assignable causes of variations (internal and external); the refusal from a traditional assumption that repetitive measurements are always normally distributed; the simple and practically convenient technique to calculate control chart limits for highly non-normal data. As the main direction for future efforts, we offer to start discussion about the implementation of Shewhart control charts into the program of school education. [ABSTRACT FROM AUTHOR]

This is an invited discussion of review paper “Nonparametric Bayesian Inference in Applications” by Peter Müller, Fernando A. Quintana and Garritt L. Page. [ABSTRACT FROM AUTHOR]

The weighted least squares estimator for model parameters was presented together with its asymptotic properties. A popular approach to optimize experimental designs called local optimal experimental designs was described together with a lesser known approach which takes into account a potential nonlinearity of the model parameters. These two approaches were combined with two different methods to solve their underlying discrete optimization problem. All presented methods were implemented in an open source MATLAB toolbox called the Optimal Experimental Design Toolbox whose structure and handling was described. In numerical experiments, the model parameters and experimental design were optimized using this toolbox. Two models for sediment concentration in seawater of different complexity served as application example. The advantages and disadvantages of the different approaches were compared, and an evaluation of the approaches was performed. [ABSTRACT FROM AUTHOR]

The article by Müller, Quintana, and Page reviews a variety of Bayesian nonparametric models and demonstrates them in a few applications. They emphasize applications in spatial data on which our discussion focuses as well. In particular, we consider two types of mixture models based on species sampling models (SSM) for spatial clustering and apply them to the Chilean mathematics testing score data analyzed by the authors. We conclude that only the mixture model of SSM with spatial locations as part of observations renders spatially non-overlapping clusters. [ABSTRACT FROM AUTHOR]

Modern cloud services are monitored by numerous multidomain and multivendor monitoring tools, which generate massive numbers of alerts and events that are not actionable. These alerts usually carry isolated messages that are missing service contexts. Administrators become inundated with tickets caused by such alert events when they are routed directly to incident management systems. Noisy alerts increase the risk of crucial warnings going undetected and leading to service outages. One of the feasible ways to cope with the above problems involves revealing the correlations behind a large number of alerts and then aggregating the related alerts according to their correlations. Based on these guidelines, AlertInsight, a framework for alert event reduction, is proposed in this paper. In AlertInsight, the correlations among event sources are found by mining a sequence of historical events. Then, event correlation knowledge is employed to build an online detector targeting the correlated events that are hidden in the event stream. Finally, the correlated events are aggregated into a single high-level event for alert reduction. Because of theweaknesses of the commonly used pairwise correlation analysis methods in complex environments, an innovative approach for multiple correlation mining, which overcomes computational complexity challenges by scanning panoramic views of historical episodes from the perspective of holism, is proposed in this paper. In addition, a neural network-based correlated event detector that can learn the event correlation knowledge generated from correlation mining and then detect the correlated events in a sequence online is proposed. Experiments are conducted to test the effectiveness of AlertInsight. The experimental results (precision=0.92, recall=0.93, and F1-score=0.93) demonstrate the performance of AlertInsight for the recognition of multiple correlated alerts and its competence for alert reduction. [ABSTRACT FROM AUTHOR]

The author comments on four articles on synthetic data published in the previous issue of the journal. These include a paper in which the idea is to produce tabulations from synthetic data to replace cells in tables from the original data as well as the use of Business Dynamics Statistics (BDS), another paper which is concerned with preserving marginal totals, and one on the computation of the probability of disclosure for individual observations.

With the arrival of Internet technology and the information era, China’s higher education has entered a new stage of development. In this context, new learning methods represented by “Internet+” have gradually emerged and rapidly spread, and traditional classroom teaching is facing a huge impact. At the same time, more and more students choose to learn independently through online courses due to resource constraints, time and space. This new learning method has posed a great challenge to the traditional education concept. Therefore, how to improve the quality of college education services has become one of the urgent problems to be solved at present. In this paper, from the perspective of service quality of college education, it is of practical significance to apply the theory of hybrid service quality to college hybrid education to explore its service quality improvement strategy. In this paper, the application of the PZB service quality model in professional education teaching is studied and discussed by using the methods of literature, mathematical statistics, and logical analysis. In this paper, the structure of the service quality evaluation system, influencing factors and results analysis, and the summary of improvement suggestions are deeply analyzed. [ABSTRACT FROM AUTHOR]

The two main parameters of grouting volume and grouting pressure are the keys to ensuring the quality of postgrouting. However, there is no equation for predicting the main grouting parameters of long and large-diameter postgrouting drilled shafts. In this paper, field data of 708 shafts in 128 projects were systematically investigated utilizing mathematical statistics, and equations for predicting the grouting volume and grouting termination pressure of long and large-diameter drilled shafts suitable for various soil layers were proposed. The range of coefficients of the grouting volume classified by soil types was defined. When establishing the equation for predicting the grouting termination pressure for a long drilled shaft, the influences of the cement grout weight in the grout pipe and the height difference between the pressure sensor and the grout valve on the grouting pressure were considered. Taking the grouting pressure and grouting volume as the control conditions of postgrouting operation, the criteria conditions for terminating postgrouting were proposed.The proposed equations for predicting the grouting volume and grouting termination pressure were verified based on a project case study. The factors affecting the grouting termination pressure were analyzed in detail. These research results were of great significance to the design of postgrouting drilled shafts. [ABSTRACT FROM AUTHOR]

Accessible Summary: What is known on the subject: Restraining and secluding health consumers for safety reasons continue to be used in psychiatric inpatient facilities even though they have no therapeutic value and have negative effects on consumers, families and staff.Six Core Strategies (6CS) for reducing seclusion and restraint have been developed to address this problem but there are very few effectiveness studies in inpatient adolescent psychiatric facilities. What the paper adds to existing knowledge: We used a mixed methods approach to evaluate the implementation of 6CS in an adolescent psychiatric facility. The implementation was successful. It eliminated the use of seclusion, substantially reduced the use of restraints and significantly reduced staff absenteeism.Using thematic analysis on feedback surveys, we identified five dominant themes that described consumers' and carers' experiences during their stay at the facility: communication, service delivery, flexibility, consistency and internal feeling states. What are the implications for practice: This study provides support for the feasibility of a comprehensive and broad‐based intervention program such as 6CS to reduce seclusion and restraint practices in inpatient mental health facilities.This study also demonstrates the value of using surveys to gather consumer and carer feedback and improve outcomes for service users. Introduction: Seclusion and restraint practices are routinely used in psychiatric facilities but are controversial for ethical, legal and safety reasons, and can cause significant harm to consumers, staff and organisations. Six Core Strategies (6CS) for reducing seclusion and restraint were developed to address this problem but very few studies have examined their effectiveness in adolescent settings. Aim/Question: To evaluate the implementation of 6CS in an adolescent inpatient psychiatric facility. Method: We retrieved archival data from an acute adolescent psychiatric ward that implemented the 6CS. Using a mixed methods approach, we evaluated outcomes on the use of seclusion and restraint, nursing staff sick leave and feedback surveys. Results: Findings showed an elimination of seclusion, and a significant reduction in restraint use and staff absenteeism in the 12 months after project implementation. Thematic analysis of feedback survey responses identified communication, service delivery, flexibility, consistency and internal feeling states as dominant themes in consumers' and carers' experience on the unit. Discussion: The 6CS is feasible and may be effective in reducing seclusion and restraint, which in turn may have a positive impact on staff wellbeing. Implications for Practice: Implementation of the 6CS with executive support, combined with staff and programmatic changes at a local level is recommended. [ABSTRACT FROM AUTHOR]

In order to analyze the driving factors of innovation and entrepreneurship, based on the time series analysis algorithm, this paper combines the analysis requirements of innovation and entrepreneurship driving factors to improve the time series, uses decomposition methods to decompose the complex original data into relatively simple components and reconstruct them, and predicts the reconstructed components to integrate the final predicted value. Moreover, this paper introduces entrepreneurial attitude as an intermediary variable and verifies it through data collection and statistical analysis, so that entrepreneurial traits influence entrepreneurial propensity through entrepreneurial attitude. The test results show that entrepreneurial attitude can better explain the influence of entrepreneurial traits on entrepreneurial propensity. In addition, this paper constructs an analysis model of driving factors for innovation and entrepreneurship, obtains experimental data through questionnaire survey methods, and conducts experimental research in combination with mathematical statistics. From the statistical results, it can be seen that the innovative and entrepreneurial driving factor analysis model based on time series analysis proposed in this paper is effective. [ABSTRACT FROM AUTHOR]

In the last two decades, survey researchers have intensively used computerised methods for the collection of different types of paradata, such as keystrokes, mouse clicks and response times, to evaluate and improve survey instruments as well as to understand the survey response process. With the growing popularity of web surveys, the importance of paradata has further increased. Within this context, response time measurement is the prevailing paradata approach. Papers typically analyse the time (measured in milliseconds or seconds) a respondent needs to answer a certain item, question, page or questionnaire. One of the key challenges when analysing the response time is to identify and separate units that are answering too quickly or too slowly. These units can have a poor response quality and are typically labelled as response time outliers. This paper focuses on approaches for identifying and processing response time outliers. It presents a systematic overview of scientific papers on response time outliers in web surveys. The key observed characteristics of the papers are the approaches used, the level of time measurement, the processing of response time outliers and the relationship between response time and response quality. The results show that knowledge on response time outliers is scattered, inconsistent and lacking systematic comparisons of approaches. Consequently, there is a need to improve and upgrade the knowledge on this issue and to develop new approaches that will overcome existing deficiencies and inconsistencies in identifying and dealing with response time outliers. [ABSTRACT FROM AUTHOR]

As a common technology product in life, display screen has been deeply embedded in various fields, and the display performance is the key indicator to determine the quality of display products. The evaluation of screen flicker is one of the key control parameters to evaluate the optical performance of the screen. As the paper introduced, commonly there are two methods of testing flicker: FMA method and JEITA method. This paper makes a research about the above two evaluation methods in time and frequency domain. Particularly, by using nonlinear regression of the mathematical statistics, this paper deduces the mathematical relationship of the two methods for the evaluating in the normal data field. Also, this paper gives accurate conversion formula and the precision analysis. By using the empirical formula, the complexity of existing test equipment can be simplified, the cost and test time can be saved greatly. [ABSTRACT FROM AUTHOR]

There is a continuing interplay between mathematics and survey methodology involving different branches of mathematics, not only probability. This interplay is quite obvious as regards the first of the two options: probability vs. non-probability sampling, as proposed and discussed in Kalton (2023). There, mathematics is represented by probability and mathematical statistics. However, sometimes connections between mathematics and survey methodology are less obvious, yet still crucial and intriguing. In this paper we refer to such an unexpected relation, namely between rotation sampling and Chebyshev polynomials. This connection, introduced in Kowalski and Wesołowski (2015), proved fundamental for the derivation of an explicit form of the recursion for the BLUE? µt of the mean on each occasion t in repeated surveys based on a cascade rotation scheme. This general result was obtained under two basic assumptions: ASSUMPTION I and ASSUMPTION II, expressed in terms of the Chebyshev polynomials. Moreover, in that paper, it was conjectured that these two assumptions are always satisfied, so the derived form of recursion is universally valid. In this paper, we partially confirm this conjecture by showing that ASSUMPTION I is satisfied for rotation patterns with a single gap of an arbitrary size. [ABSTRACT FROM AUTHOR]

This paper recommends that critical attention towards machine learning should be focused on the ordering procedures at work in these models. More precisely, it draws attention to the central role of 'latent spaces.' The paper first explores 'latent space' through a series of analogies, and then briefly situates the concept in relation to a genealogy reaching back to developments in mathematical statistics at the turn to the 20th century. [ABSTRACT FROM AUTHOR]

In recent years, deep learning has seen remarkable progress in many fields, especially with many excellent pre-training models emerged in Natural Language Processing(NLP). However, these pre-training models can not be used directly in music generation tasks due to the different representations between music symbols and text. Compared with the traditional presentation method of music melody that only includes the pitch relationship between single notes, the text-like representation method proposed in this paper contains more melody information, including pitch, rhythm and pauses, which expresses the melody in a form similar to text and makes it possible to use existing pre-training models in symbolic melody generation. In this paper, based on the generative pre-training-2(GPT-2) text generation model and transfer learning we propose MT-GPT-2(music textual GPT-2) model that is used in music melody generation. Then, a symbolic music evaluation method(MEM) is proposed through the combination of mathematical statistics, music theory knowledge and signal processing methods, which is more objective than the manual evaluation method. Based on this evaluation method and music theories, the music generation model in this paper are compared with other models (such as long short-term memory (LSTM) model,Leak-GAN model and Music SketchNet). The results show that the melody generated by the proposed model is closer to real music. [ABSTRACT FROM AUTHOR]

Background: There is a need to detect and prevent fluid overload and malnutrition in heart failure. Bioelectrical impedance analysis and bioelectrical impedance vector analysis are medical instruments that can advance heart failure management by generating values of body composition and body water, assisting clinicians to detect fluid and nutritional status. However, there is a lack of evidence to summarise how they have been used among heart failure patients. Method: A systematic search was conducted. Result: Two hundred and four papers were screened. Forty-eight papers were reviewed, and 46 papers were included in this review. The literature shows that bioelectrical impedance analysis and bioelectrical impedance vector analysis were mostly used to assess fluid and nutritional status, together with diagnostic and prognostic values. Contraindication of using BIA and implications for practice are also demonstrated. Conclusion: The findings suggest that bioelectrical impedance vector analysis is superior to bioelectrical impedance analysis when assessing hydration/nutritional status in heart failure. Assessing a patient using bioelectrical impedance analysis/bioelectrical impedance vector analysis, together with natriuretic peptide -heart failure biomarkers, increases the diagnostic accuracy of heart failure. Further studies are required to examine the cost effectiveness of using these instruments in clinical practice. [ABSTRACT FROM AUTHOR]

This article presents and investigates a modified version of the Weibull distribution that incorporates four parameters and can effectively represent a hazard rate function with a shape resembling a bathtub. Its significance in the fields of lifetime and reliability stems from its ability to model both increasing and decreasing failure rates. The proposed distribution encompasses several well-known models such as the Weibull, extreme value, exponentiated Weibull, generalized Rayleigh, and modified Weibull distributions. The paper derives key mathematical statistics of the proposed distribution, including the quantile function, moments, moment-generating function, and order statistics density. Various mathematical properties of the proposed model are established, and the unknown parameters of the distribution are estimated using different estimation techniques. Furthermore, the effectiveness of these estimators is assessed through numerical simulation studies. Finally, the paper applies the new model and compares it with various existing distributions by analyzing two real-life time data sets. [ABSTRACT FROM AUTHOR]

This paper investigated the Kronecker product (KP) decomposition of the Boolean matrix and analyzed the topological structure of Kronecker product Boolean networks (KPBNs). First, the support matrix set of the Boolean matrix consisting of support matrices was defined. Second, a verifiable condition was presented for the KP decomposition of the Boolean matrix based on the support matrices. Third, the equivalence of KP decomposition between the Boolean matrix and support matrix set was established. Finally, the KP decomposition of Boolean matrix was used to analyze the topological structure of KPBNs. It was shown that the topological structure of KPBNs can be determined by that of the factor of Boolean networks (BNs). [ABSTRACT FROM AUTHOR]