• 제목/요약/키워드: Performance-based Statistics

검색결과 1,048건 처리시간 0.021초

Positive and negative predictive values by the TOC curve

  • Hong, Chong Sun;Choi, So Yeon
    • Communications for Statistical Applications and Methods
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    • 제27권2호
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    • pp.211-224
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    • 2020
  • Sensitivity and specificity are popular measures described by the receiver operating characteristic (ROC) curve. There are also two other measures such as the positive predictive value (PPV) and negative predictive value (NPV); however, the PPV and NPV cannot be represented by the ROC curve. Based on the total operating characteristic (TOC) curve suggested by Pontius and Si (International Journal of Geographical Information Science, 97, 570-583, 2014), explanatory methods are proposed to geometrically describe the PPV and NPV by the TOC curve. It is found that the PPV can be regarded as the slope of the right-angled triangle connecting the origin to a certain point on the TOC curve, while 1 - NPV can be represented as the slope of the right-angled triangle connecting a certain point to the top right corner of the TOC curve. When the neutral zone exists, the PPV and 1-NPV can be described as the slopes of two other right-angled triangles of the TOC curve. Therefore, both the PPV and NPV can be estimated using the TOC curve, whether or not the neutral zone is present.

센서 레지스트리 시스템의 처리 성능 개선을 위한 모바일 앱 프로파일 기반 센서 필터링 (Sensor Filtering based on Mobile App Profiles for Enhancing the Processing Performance of Sensor Registry System)

  • 정동원;유현석;이석훈
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2015년도 춘계학술발표대회
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    • pp.273-276
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    • 2015
  • 논문에서는 센서 레지스트리 시스템의 성능 개성을 위한 센서 필터링 기법을 제안한다. 센서 레지스트리 시스템은 이질적인 센서 네트워크 환경에서, 즉시적인 센서 데이터의 의미 해석 및 처리를 위한 시스템이다. 센서 레지스트리 시스템은 다양한 장점을 제공하지만 여전히 처리 성능 측면에서 개선이 요구된다. 이 논문에서는 센서 레지스트리 시스템의 불필요한 센서 데이터를 여과하여 처리 속도를 향상시키기 위해 모바일 앱 프로파일을 이용한다. 제안 방법은 기존 센서 레지스트리 시스템의 모바일 기기 측에서 센서 필터링 연산을 수행하게 되며 이를 통해 전체적인 성능을 향상시킨다.

Linear regression under log-concave and Gaussian scale mixture errors: comparative study

  • Kim, Sunyul;Seo, Byungtae
    • Communications for Statistical Applications and Methods
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    • 제25권6호
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    • pp.633-645
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    • 2018
  • Gaussian error distributions are a common choice in traditional regression models for the maximum likelihood (ML) method. However, this distributional assumption is often suspicious especially when the error distribution is skewed or has heavy tails. In both cases, the ML method under normality could break down or lose efficiency. In this paper, we consider the log-concave and Gaussian scale mixture distributions for error distributions. For the log-concave errors, we propose to use a smoothed maximum likelihood estimator for stable and faster computation. Based on this, we perform comparative simulation studies to see the performance of coefficient estimates under normal, Gaussian scale mixture, and log-concave errors. In addition, we also consider real data analysis using Stack loss plant data and Korean labor and income panel data.

Quantile confidence region using highest density

  • Hong, Chong Sun;Yoo, Myung Soo
    • Communications for Statistical Applications and Methods
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    • 제26권1호
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    • pp.35-46
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    • 2019
  • Multivariate Confidence Region (MCR) cannot be used to obtain the confidence region of the mean vector of multivariate data when the normality assumption is not satisfied; however, the Quantile Confidence Region (QCR) could be used with a Multivariate Quantile Vector in these cases. The coverage rate of the QCR is better than MCR; however, it has a disadvantage because the QCR has a wide shape when the probability density function follows a bimodal form. In this study, we propose a Quantile Confidence Region using the Highest density (QCRHD) method with the Highest Density Region (HDR). The coverage rate of QCRHD was superior to MCR, but is found to be similar to QCR. The QCRHD is constructed as one region similar to QCR when the distance of the mean vector is close. When the distance of the mean vector is far, the QCR has one wide region, but the QCRHD has two smaller regions. Based on these features, it is found that the QCRHD can overcome the disadvantages of the QCR, which may have a wide shape.

Pliable regression spline estimator using auxiliary variables

  • Oh, Jae-Kwon;Jhong, Jae-Hwan
    • Communications for Statistical Applications and Methods
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    • 제28권5호
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    • pp.537-551
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    • 2021
  • We conducted a study on a regression spline estimator with a few pre-specified auxiliary variables. For the implementation of the proposed estimators, we adapted a coordinate descent algorithm. This was implemented by considering a structure of the sum of the residuals squared objective function determined by the B-spline and the auxiliary coefficients. We also considered an efficient stepwise knot selection algorithm based on the Bayesian information criterion. This was to adaptively select smoothly functioning estimator data. Numerical studies using both simulated and real data sets were conducted to illustrate the proposed method's performance. An R software package psav is available.

개별 관측치에 대한 관리도 비교 (Comparison of control charts for individual observations)

  • 이성임
    • 응용통계연구
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    • 제35권2호
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    • pp.203-215
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    • 2022
  • 본 논문에서는 연속적으로 관측되는 개별 관측치에 대하여, 모평균의 변화를 모니터링하는 데 적용 가능한 관리도에 대하여 고찰해 보고자 한다. 가장 대표적인 관리도로 슈하르트의 X 관리도, 지수가중이동평균 관리도와 이들의 결합관리도에 관하여 살펴보고 모의실험을 통하여 각 관리도의 성능을 비교 평가해 보고자 한다. 또한, 실제 자료분석을 통해 실질적인 문제에서 관리도를 어떻게 사용해야 하는지 알아보고, 각 관리도의 문제점에 대하여 살펴보기로 한다.

Naive Bayes classifiers boosted by sufficient dimension reduction: applications to top-k classification

  • Yang, Su Hyeong;Shin, Seung Jun;Sung, Wooseok;Lee, Choon Won
    • Communications for Statistical Applications and Methods
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    • 제29권5호
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    • pp.603-614
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    • 2022
  • The naive Bayes classifier is one of the most straightforward classification tools and directly estimates the class probability. However, because it relies on the independent assumption of the predictor, which is rarely satisfied in real-world problems, its application is limited in practice. In this article, we propose employing sufficient dimension reduction (SDR) to substantially improve the performance of the naive Bayes classifier, which is often deteriorated when the number of predictors is not restrictively small. This is not surprising as SDR reduces the predictor dimension without sacrificing classification information, and predictors in the reduced space are constructed to be uncorrelated. Therefore, SDR leads the naive Bayes to no longer be naive. We applied the proposed naive Bayes classifier after SDR to build a recommendation system for the eyewear-frames based on customers' face shape, demonstrating its utility in the top-k classification problem.

Associativity-Based On-Demand Multi-Path Routing In Mobile Ad Hoc Networks

  • Rehman, Shafqat Ur;Song, Wang-Cheol;Park, Gyung-Leen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제3권5호
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    • pp.475-491
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    • 2009
  • This paper is primarily concerned with multi-path routing in Mobile Ad hoc Networks (MANETs). We propose a novel associativity-based on-demand source routing protocol for MANETs that attempts to establish relatively stable path(s) between the source and the destination. We introduce a new notion for gauging the temporal and spatial stability of nodes, and hence the paths interconnecting them. The proposed protocol is compared with other unipath (DSDV and AODV) and multi-path (AOMDV) routing protocols. We investigate the performance in terms of throughput, normalized routing overhead, packet delivery ratio etc. All on-demand protocols show good performance in mobile environments with less traffic overhead compared to proactive approaches, but they are prone to longer end-to-end delays due to route discovery and maintenance.

부·모의 양육행동이 유아의 실행기능에 미치는 영향 (The Effects of Parenting Behaviors on Preschoolers' Executive Function)

  • 이윤정;공영숙;임지영
    • 가정과삶의질연구
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    • 제32권1호
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    • pp.13-26
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    • 2014
  • The purpose of this study was to explore the effects of parenting behaviors on preschoolers' executive function, focusing on methods of measuring executive function. The subjects of this study were 166 preschoolers who were 3 to 5 years of age, and their parents. Data were collected by various performance-based tests and their parents' reports and analyzed by descriptive statistics and hierarchical linear regression analysis using the SPSS 19.0 program. The major results were as follows: First, maternal autonomous and paternal affective parenting behaviors significantly affected preschoolers' performance-based executive function. Second, maternal affective parenting behaviors significantly affected preschoolers' parent-report executive function. The results suggest the importance of positive parenting practices in the development of preschoolers' executive function.

PPD: A Robust Low-computation Local Descriptor for Mobile Image Retrieval

  • Liu, Congxin;Yang, Jie;Feng, Deying
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제4권3호
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    • pp.305-323
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    • 2010
  • This paper proposes an efficient and yet powerful local descriptor called phase-space partition based descriptor (PPD). This descriptor is designed for the mobile image matching and retrieval. PPD, which is inspired from SIFT, also encodes the salient aspects of the image gradient in the neighborhood around an interest point. However, without employing SIFT's smoothed gradient orientation histogram, we apply the region based gradient statistics in phase space to the construction of a feature representation, which allows to reduce much computation requirements. The feature matching experiments demonstrate that PPD achieves favorable performance close to that of SIFT and faster building and matching. We also present results showing that the use of PPD descriptors in a mobile image retrieval application results in a comparable performance to SIFT.