• Title/Summary/Keyword: record value statistics

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CHARACTERIZATIONS OF THE EXPONENTIAL DISTRIBUTION BY ORDER STATISTICS AND CONDITIONAL

  • Lee, Min-Young;Chang, Se-Kyung;Jung, Kap-Hun
    • Communications of the Korean Mathematical Society
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    • v.17 no.3
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    • pp.535-540
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    • 2002
  • Let X$_1$, X$_2$‥‥,X$\_$n/ be n independent and identically distributed random variables with continuous cumulative distribution function F(x). Let us rearrange the X's in the increasing order X$\_$1:n/ $\leq$ X$\_$2:n/ $\leq$ ‥‥ $\leq$ X$\_$n:n/. We call X$\_$k:n/ the k-th order statistic. Then X$\_$n:n/ - X$\_$n-1:n/ and X$\_$n-1:n/ are independent if and only if f(x) = 1-e(equation omitted) with some c > 0. And X$\_$j/ is an upper record value of this sequence lf X$\_$j/ > max(X$_1$, X$_2$,¨¨ ,X$\_$j-1/). We define u(n) = min(j|j > u(n-1),X$\_$j/ > X$\_$u(n-1)/, n $\geq$ 2) with u(1) = 1. Then F(x) = 1 - e(equation omitted), x > 0 if and only if E[X$\_$u(n+3)/ - X$\_$u(n)/ | X$\_$u(m)/ = y] = 3c, or E[X$\_$u(n+4)/ - X$\_$u(n)/|X$\_$u(m)/ = y] = 4c, n m+1.

Infinite Failure NHPP Software Mixture Reliability Growth Model Base on Record Value Statistics (기록값 통계량에 기초한 무한고장 NHPP 소프트웨어 혼합 신뢰성장 모형에 관한 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul;Kim, Kyung-Soo
    • Convergence Security Journal
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    • v.7 no.3
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    • pp.51-60
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    • 2007
  • Infinite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, exponential distribution and Rayleigh distribution model was reviewed, proposes the mixture reliability model, which made out efficiency substituted for situation for failure time Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using S27 data set for the sake of proposing shape parameter of the mixture distribution was employed. This analysis of failure data compared with the mixture distribution model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

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Estimation of a Nationwide Statistics of Hernia Operation Applying Data Mining Technique to the National Health Insurance Database (데이터마이닝 기법을 이용한 건강보험공단의 수술 통계량 근사치 추정 -허니아 수술을 중심으로-)

  • Kang, Sung-Hong;Seo, Seok-Kyung;Yang, Yeong-Ja;Lee, Ae-Kyung;Bae, Jong-Myon
    • Journal of Preventive Medicine and Public Health
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    • v.39 no.5
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    • pp.433-437
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    • 2006
  • Objectives: The aim of this study is to develop a methodology for estimating a nationwide statistic for hernia operations with using the claim database of the Korea Health Insurance Cooperation (KHIC). Methods: According to the insurance claim procedures, the claim database was divided into the electronic data interchange database (EDI_DB) and the sheet database (Paper_DB). Although the EDI_DB has operation and management codes showing the facts and kinds of operations, the Paper_DB doesn't. Using the hernia matched management code in the EDI_DB, the cases of hernia surgery were extracted. For drawing the potential cases from the Paper_DB, which doesn't have the code, the predictive model was developed using the data mining technique called SEMMA. The claim sheets of the cases that showed a predictive probability of an operation over the threshold, as was decided by the ROC curve, were identified in order to get the positive predictive value as an index of usefulness for the predictive model. Results: Of the claim databases in 2004, 14,386 cases had hernia related management codes with using the EDI system. For fitting the models with applying the data mining technique, logistic regression was chosen rather than the neural network method or the decision tree method. From the Paper_DB, 1,019 cases were extracted as potential cases. Direct review of the sheets of the extracted cases showed that the positive predictive value was 95.3%. Conclusions: The results suggested that applying the data mining technique to the claim database in the KHIC for estimating the nationwide surgical statistics would be useful from the aspect of execution and cost-effectiveness.

Use of beta-P distribution for modeling hydrologic events

  • Murshed, Md. Sharwar;Seo, Yun Am;Park, Jeong-Soo;Lee, Youngsaeng
    • Communications for Statistical Applications and Methods
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    • v.25 no.1
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    • pp.15-27
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    • 2018
  • Parametric method of flood frequency analysis involves fitting of a probability distribution to observed flood data. When record length at a given site is relatively shorter and hard to apply the asymptotic theory, an alternative distribution to the generalized extreme value (GEV) distribution is often used. In this study, we consider the beta-P distribution (BPD) as an alternative to the GEV and other well-known distributions for modeling extreme events of small or moderate samples as well as highly skewed or heavy tailed data. The L-moments ratio diagram shows that special cases of the BPD include the generalized logistic, three-parameter log-normal, and GEV distributions. To estimate the parameters in the distribution, the method of moments, L-moments, and maximum likelihood estimation methods are considered. A Monte-Carlo study is then conducted to compare these three estimation methods. Our result suggests that the L-moments estimator works better than the other estimators for this model of small or moderate samples. Two applications to the annual maximum stream flow of Colorado and the rainfall data from cloud seeding experiments in Southern Florida are reported to show the usefulness of the BPD for modeling hydrologic events. In these examples, BPD turns out to work better than $beta-{\kappa}$, Gumbel, and GEV distributions.

A Study on Optimal Release Time for Software Systems based on Generalized Gamma Distribution (일반화 감마분포에 근거한 소프트웨어 최적방출시기에 관한 비교 연구)

  • Kim, Jae-Wook;Kim, Hee-Cheul
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.6 no.1
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    • pp.55-67
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    • 2010
  • Decision problem called an optimal release policies, after testing a software system in development phase and transfer it to the user, is studied. The applied model of release time exploited infinite non-homogeneous Poisson process. This infinite non-homogeneous Poisson process is a model which reflects the possibility of introducing new faults when correcting or modifying the software. The failure life-cycle distribution used generalized gamma type distribution which has the efficient various property because of various shape and scale parameter. Thus, software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement becomes an optimal release policies. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, estimated software optimal release time.

The Comparative Study of Software Optimal Release Time Based on Record Value Statistics (기록값 통계량을 이용한 소프트웨어 최적 방출시기에 관한 비교 연구)

  • Kim, Hee-Cheul;Park, Hyoung-Keun
    • Proceedings of the KAIS Fall Conference
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    • 2009.05a
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    • pp.659-662
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    • 2009
  • 본 연구에서는 소프트웨어 제품을 개발하여 테스팅을 거친 후 사용자에게 인도하는 시기를 결정하는 방출문제에 대하여 연구되었다. 소프트웨어의 결함을 제거하거나 수정 작업 중에도 새로운 결함이 발생될 가능성이 있는 무한고장수를 가진 비동질적인 포아송 과정에 기초하고 수명분포는 신뢰도 측면에서 여러 분포들을 적합시키는데 효율적인 특성을 가진 와이블분포를 이용한 최적 방출시기에 관한 문제를 제시하여 소프트웨어 요구 신뢰도를 만족시키고 소프트웨어 개발 및 유지 총비용을 최소화 시키는 최적 소프트웨어 방출 정책에 대하여 논의되었다.

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The Effects of Store Attributes on Customer Equity of Dongdaemun Shopping Malls - Focusing on Dongdaemun Shopping Mall Types - (동대문 쇼핑몰 선택속성이 고객자산에 미치는 영향 - 동대문 쇼핑몰의 유형을 중심으로 -)

  • Zhang, Ting;Ko, Eunju;Chae, Heeju
    • Fashion & Textile Research Journal
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    • v.18 no.4
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    • pp.438-449
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    • 2016
  • Domestic and foreign tourism authorities show that the most favorite tourist activity is shopping. Tourism income in Korea set a record in 2014 due to a large influx of Chinese tourists. Dongdaemun fashion market was selected as the most preferred destination for Chinese tourists shopping in Korea. This study examines the effect of store attributes on customer equity at Dongdaemun shopping malls. This study adopted a survey; subsequently, 637 questionnaires were used in the final analysis. Collected data were analyzed using SPSS 21.0 and AMOS 18.0 statistics program. The main findings of this study are as follows. Among the three store attributes of Dongdaemun shopping malls, service and environment attributes appeared to influence the three drivers of consumer equity. In addition, value equity was identified to provide a positive impact on Customer Lifetime Value (CLV), brand equity, and relationship equity were identified as having a positive impact on revisit intention. Second, the relationships between the variables were significantly different in two types of the Dongdaemun fashion shopping mall (Doota vs Lotte Fitin). In addition, this study offers a valuable implication for brand marketers to maintain and develop customer equity in Dongdaemun fashion markets.

Validity of Self-reported Stroke and Myocardial Infarction in Korea: The Health Examinees (HEXA) Study

  • Choe, Sunho;Lee, Joonki;Lee, Jeeyoo;Kang, Daehee;Lee, Jong-Koo;Shin, Aesun
    • Journal of Preventive Medicine and Public Health
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    • v.52 no.6
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    • pp.377-383
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    • 2019
  • Objectives: Self-reported disease history is often used in epidemiological studies. In this study, we acquired the hospital records of subjects who self-reported stroke or myocardial infarction (MI) and evaluated the validity of the participants' self-reported disease history. We also determined the level of agreement between specialists and non-specialists. Methods: Among the participants in the Health Examinees study, 1488 subjects self-reported stroke or MI during 2012-2017, and medical records were acquired for the 429 subjects (28.8%) who agreed to share their medical information. Each record was independently assigned to 2 medical doctors for review. The records were classified as 'definite,' 'possible,' or 'not' stroke or MI. If the doctors did not agree, a third doctor made the final decision. The positive predictive value (PPV) of self-reporting was calculated with the doctors' review as the gold standard. Kappa statistics were used to compare the results between general doctors and neurologists or cardiologists. Results: Medical records from 208 patients with self-reported stroke and 221 patients with self-reported MI were reviewed. The PPV of self-reported disease history was 51.4% for stroke and 32.6% for MI. If cases classified as 'possible' were counted as positive diagnoses, the PPV was 59.1% for stroke and 33.5% for MI. Kappa statistics showed moderate levels of agreement between specialists and nonspecialists for both stroke and MI. Conclusions: The validity of self-reported disease was lower than expected, especially in those who reported having been diagnosed with MI. Proper consideration is needed when using these self-reported data in further studies.

A Study on the Relation between Occlusal Wear Area and Occlusal Contact Patterns (교모면적과 교합접촉양태 간의 관계에 대한 연구)

  • Se-Sook Kang;Kyung-Soo Han
    • Journal of Oral Medicine and Pain
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    • v.19 no.2
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    • pp.153-168
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    • 1994
  • The aim of the present study was to investigate a relation between occlusal wear area and occlusal contact patterns. For the purpose, occlusal wear area were measured in 58 dental students and in 129 patients with temporomandibular disorders(TMDs) from dental casts. Teeth used in this study were from canine to second molar on both sides in upper arch, totally ten. Occlusal wear area on casts was marked by pencil and photocopies, and then, the area was measured with planimeter. Occlusal relation was clinically examined with regard to Angle's classification, chewing side preference, lateral guidance pattern and bruxing and/or clenching habit. T-Scan, electronic occlusal contact analyzer, was used to record occlusal contact number, contact force, contact time and occlusal balance that is TLR(total left-right statistics) during tooth contact. All measurement were repeated 3 times and the average value was used for data processing. The obtained results were as follows : 1. Mean value of occlusal wear area did not differ significantly between dental students and patients. 2. There ws not significant difference in wear area between chewing side and non-chewing side in both groups. 3. Occlusal wear area was significantly increased with age in both groups. 4. Three subgroups divided by Angle's classification did not show any difference in occlusal wear area among them, but three subgroups divided by lateral guidance pattern showed slightly significant difference between canine guide subgroup and group function subgroup in patients. Occlusal wear ares\a in group function subgroup wear larger than canine guide subgroup. 5. Mean value of wear area in patients with bruxing and/or clenching habit did not differ from those in patients without such habit. 6. Correlationship among items related to occlusal contact pattern were highly consistent and significant in dental students and only one item significantly correlated with occlusal wear area was tooth contact time.

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CANCER CLASSIFICATION AND PREDICTION USING MULTIVARIATE ANALYSIS

  • Shon, Ho-Sun;Lee, Heon-Gyu;Ryu, Keun-Ho
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.706-709
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    • 2006
  • Cancer is one of the major causes of death; however, the survival rate can be increased if discovered at an early stage for timely treatment. According to the statistics of the World Health Organization of 2002, breast cancer was the most prevalent cancer for all cancers occurring in women worldwide, and it account for 16.8% of entire cancers inflicting Korean women today. In order to classify the type of breast cancer whether it is benign or malignant, this study was conducted with the use of the discriminant analysis and the decision tree of data mining with the breast cancer data disclosed on the web. The discriminant analysis is a statistical method to seek certain discriminant criteria and discriminant function to separate the population groups on the basis of observation values obtained from two or more population groups, and use the values obtained to allow the existing observation value to the population group thereto. The decision tree analyzes the record of data collected in the part to show it with the pattern existing in between them, namely, the combination of attribute for the characteristics of each class and make the classification model tree. Through this type of analysis, it may obtain the systematic information on the factors that cause the breast cancer in advance and prevent the risk of recurrence after the surgery.

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