• Title/Summary/Keyword: 모수 추정법

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Simulation Study on Model Selection Based on AIC under Unbalanced Design in Linear Mixed Effect Models (불균형 자료에서 AIC를 이용한 선형혼합모형 선택법의 효율에 대한 모의실험 연구)

  • Lee, Yong-Hee
    • The Korean Journal of Applied Statistics
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    • v.23 no.6
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    • pp.1169-1178
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    • 2010
  • This article consider a performance model selection based on AIC under unbalanced deign in linear mixed effect models. Vaida and Balanchard (2005) proposed conditional AIC for model selection in linear mixed effect models when the prediction of random effects is of primary interest. Theoretical properties of cAIC and related criteria have been investigated by Liang et al. (2008) and Greven and Kneib (2010). However, all of the simulation studies were performed under a balanced design. Even though functional form of AIC remain same even under the unbalanced deign, it is worthwhile to investigate performance of AIC based model selection criteria under the unbalanced design. The simulation study in this article shows how unbalancedness affects model selection in linear mixed effect models.

Development of epidemic model using the stochastic method (확률적 방법에 기반한 질병 확산 모형의 구축)

  • Ryu, Soorack;Choi, Boseung
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.2
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    • pp.301-312
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    • 2015
  • The purpose of this paper is to establish the epidemic model to explain the process of disease spread. The process of disease spread can be classified into two types: deterministic process and stochastic process. Most studies supposed that the process follows the deterministic process and established the model using the ordinary differential equation. In this article, we try to build the disease spread prediction model based on the SIR (Suspectible - Infectious - Recovered) model. we first estimated the model parameters using least squared method and applied to a deterministic model using ordinary differential equation. we also applied to a stochastic model based on Gillespie algorithm. The methods introduced in this paper are applied to the data on the number of cases of malaria every week from January 2001 to March 2003, released by Korea Centers for Disease Control and Prevention. As a result, we conclude that our model explains well the process of disease spread.

The Comparative Study for Software Reliability Model Based on Finite and Infinite Failure Exponential Power NHPP (유한 및 무한고장 지수파우어 NHPP 소프트웨어 신뢰성모형에 대한 비교 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.8 no.3
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    • pp.195-202
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    • 2015
  • NHPP software reliability models for failure analysis can have, in the literature, exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, finite failure NHPP models that assuming the expected value of the defect and infinite failures NHPP models that repairing software failure point in time reflects the situation, were presented for comparing property. Commonly used in the field of software reliability based on exponential power distribution software reliability model finite failures and infinite failures were presented for comparison problem. As a result, finite fault model is effectively infinite fault models, respectively. The parameters estimation using maximum likelihood estimation was conducted. In this research, software developers to identify software failure property some extent be able to help is considered.

Comparing MCMC algorithms for the horseshoe prior (Horseshoe 사전분포에 대한 MCMC 알고리듬 비교 연구)

  • Miru Ma;Mingi Kang;Kyoungjae Lee
    • The Korean Journal of Applied Statistics
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    • v.37 no.1
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    • pp.103-118
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    • 2024
  • The horseshoe prior is notably one of the most popular priors in sparse regression models, where only a small fraction of coefficients are nonzero. The parameter space of the horseshoe prior is much smaller than that of the spike and slab prior, so it enables us to efficiently explore the parameter space even in high-dimensions. However, on the other hand, the horseshoe prior has a high computational cost for each iteration in the Gibbs sampler. To overcome this issue, various MCMC algorithms for the horseshoe prior have been proposed to reduce the computational burden. Especially, Johndrow et al. (2020) recently proposes an approximate algorithm that can significantly improve the mixing and speed of the MCMC algorithm. In this paper, we compare (1) the traditional MCMC algorithm, (2) the approximate MCMC algorithm proposed by Johndrow et al. (2020) and (3) its variant in terms of computing times, estimation and variable selection performance. For the variable selection, we adopt the sequential clustering-based method suggested by Li and Pati (2017). Practical performances of the MCMC methods are demonstrated via numerical studies.

A Review on the Sampling Design for Energy Consumption Survey in Agricultural Sector (농업부문 에너지 소비량 조사를 위한 표본설계)

  • Kim, Yean-Jung;Kim, Bae-Sung
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.9
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    • pp.411-417
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    • 2017
  • It is necessary to determine the current and future energy consumption by farm households for the rational specification of energy related policy in the Korean agricultural sector. Especially, It is important to identify the consumption by source of energy and by the crops. On the other hand, the world has tried to reduce the production of greenhouse gases and, in line with this, the Korean government established related legislations to contribute to this reduction (30% reduction in emissionsby 2020). The reduction target of the agricultural sector is specified as 5.2% of the national total. This study focuses on sampling design to determine the energy consumption and emission of greenhouse gases, and suggests several alternatives to improve the confidence level and to make a dent survey and estimation errors. The population for the energy consumption survey of the agricultural sector was derived from agricultural census data. In the case of commodities with high skewness, we cut the sample range to within the statistical significant range. The number of samples in each class is specified using the Neyman allocation method and 95% significance level. The estimation results are compared with the population to verify the statistical significance and several management methods of sampling errors are suggested.

Genetic Analysis of Some Polymorphic Isozymes in Pinus densiflora(II) - Inheritance of acid phosphatase, alcohol dehydrogenase and catalase isozymes - (소나무의 몇가지 다형적(多形的) 동위효소(同位酵素)의 유전분석(遺傳分析)(II) - Acid phosphatase, alcohol dehydrogenase와 catalase 동위효소(同位酵素)의 유전양식(遺傳樣式) -)

  • Kim, Z.S.;Hong, Y.P.
    • Journal of Korean Society of Forest Science
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    • v.68 no.1
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    • pp.32-36
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    • 1985
  • Megagametophyte tissues of Pinus densiflora were subjected to study the inheritance of acid phosphatase (ACP), alcohol dehydrogenase (ADH) and catalase (CAT) isozymes by starch gel zone-electrophoresis. At least three or four zones were segregated for ACP isozyme. However, as one isozyme of ACP-A zone was separated clearly, only that isozyme was analysed. Five isozyme phenotypes (A1-A5), observed in ACP-A zone, were segregated to a simple Mendelian ratio, suggesting that these are controlled by five codominant alleles existed at ACP-A locus. Two zones of activity were segregated in the gels after staining for ADH, the more anodal zone (ADH-A) of the two was invariant in our materials. Three isozyme phenotypes (B1-B3) were observed in ADH-B zone and these variants showed a 1:1 segregation pattern, suggesting that each variant is controlled by three codominant alleles at ADH-B locus. A total of five isozyme phenotypes, composed of multiple bands, were observed in CAT isozyme. The segregation of these phenotypes in heterozygous trees did not show any significant deviation from a 1:1 segregation. Therefore, the genetic control of CAT isozyme in Pinus densiflora seeds seems to be based on a single locus (CAT-A) with Five codominant alleles ($A_1-A_5$).

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Groundwater level behavior analysis using kernel density estimation (비모수 핵밀도 함수를 이용한 지하수위 거동분석)

  • Jeong, Ji Hye;Kim, Jong Wook;Lee, Jeong Ju;Chun, Gun Il
    • Proceedings of the Korea Water Resources Association Conference
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    • 2017.05a
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    • pp.381-381
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    • 2017
  • 수자원 분야에 대한 기후변화의 영향은 홍수, 가뭄 등 극치 수문사상의 증가와 변동성 확대를 초래하는 것으로 알려져 있으며, 이에 따라 예년에 비해 발생빈도 및 심도가 증가한 가뭄에 대한 모니터링 및 피해경감을 위해 정부에서는 국민안전처를 비롯한 관계기관 합동으로 생활 공업 농업용수 등 분야별 가뭄정보를 제공하고 있다. 국토교통부와 환경부는 생활 및 공업용수 분야의 가뭄정보 제공을 위해 광역 지방 상수도를 이용하는 급수 지역과 마을상수도, 소규모급수시설 등 미급수지역의 용수수급 정보를 분석하여 가뭄 분석정보를 제공 중에 있다. 하지만, 미급수지역에 대한 가뭄 예?경보는 기준이 되는 수원정보의 부재로 기상 가뭄지수인 SPI6를 이용하여 정보를 생산하고 있다. 기상학적 가뭄 상황과 물부족에 의한 체감 가뭄은 차이가 있으며, 미급수 지역의 경우 지하수를 주 수원으로 사용하는 지역이 대부분으로 기상학적 가뭄지수인 SPI6를 이용한 가뭄정보로 실제 물수급 상황을 반영하기는 부족한 실정이다. 따라서 본 연구에서는 미급수지역의 주요 수원인 지하수의 수위 상황을 반영한 가뭄모니터링 기법을 개발하고자 하였으며, 가용량 분석이 현실적으로 어려운 지하수의 특성을 고려하여 수위 거동의 통계적 분석을 통해 가뭄을 모니터링 할 수 있는 방법으로 접근하였다. 국가지하수관측소 중 관측기간이 10년 이상이고 강우와의 상관성이 높은 관측소들을 선정한 후, 일수위 관측자료를 월별로 분리하여 1월~12월 각 월에 대해 핵밀도 함수 추정기법(kernel densitiy estimation)을 적용하여 월별 지하수위 분포 특성을 도출하였다. 각 관측소별 관측수위 분포에 대해 백분위수(percentile)를 이용하여, 25%~100% 사이는 정상, 10%~25% 사이는 주의단계, 5%~10% 사이는 심한가뭄, 5% 이하는 매우심함으로 가뭄의 단계를 구분하였다. 각 백분위수에 해당하는 수위 값은 추정된 Kernel Density와 Quantile Function을 이용하여 산정하였고, 최근 10일 평균수위를 현재의 수위로 설정하여 가뭄의 정도를 분류하였다. 분석된 결과는 관측소를 기점으로 역거리가중법(inverse distance weighting)을 통해 공간 분포를 시켰으며, 수문학적, 지질학적 동질성을 반영하기 위하여 유역도 및 수문지질도를 중첩한 공간연산을 통해 전국 지하수 가뭄상태를 나타내는 지하수위 등급분포도를 작성하였다. 실제 가뭄상황과의 상관성을 분석하기 위해 언론기사를 통해 확인된 가뭄시기와 백문위수 25%이하로 분석된 지하수 가뭄시기를 ROC(receiver operation characteristics) 분석을 통해 비교 검증하였다.

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Software Reliability Growth Modeling in the Testing Phase with an Outlier Stage (하나의 이상구간을 가지는 테스팅 단계에서의 소프트웨어 신뢰도 성장 모형화)

  • Park, Man-Gon;Jung, Eun-Yi
    • The Transactions of the Korea Information Processing Society
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    • v.5 no.10
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    • pp.2575-2583
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    • 1998
  • The productionof the highly relible softwae systems and theirs performance evaluation hae become important interests in the software industry. The software evaluation has been mainly carried out in ternns of both reliability and performance of software system. Software reliability is the probability that no software error occurs for a fixed time interval during software testing phase. These theoretical software reliability models are sometimes unsuitable for the practical testing phase in which a software error at a certain testing stage occurs by causes of the imperfect debugging, abnornal software correction, and so on. Such a certatin software testing stage needs to be considered as an outlying stage. And we can assume that the software reliability does not improve by means of muisance factor in this outlying testing stage. In this paper, we discuss Bavesian software reliability growth modeling and estimation procedure in the presence of an imidentitied outlying software testing stage by the modification of Jehnski Moranda. Also we derive the Bayes estimaters of the software reliability panmeters by the assumption of prior information under the squared error los function. In addition, we evaluate the proposed software reliability growth model with an unidentified outlying stage in an exchangeable model according to the values of nuisance paramether using the accuracy, bias, trend, noise metries as the quantilative evaluation criteria through the compater simulation.

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Bivariate Frequency Analysis of Rainfall using Copula Model (Copula 모형을 이용한 이변량 강우빈도해석)

  • Joo, Kyung-Won;Shin, Ju-Young;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.45 no.8
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    • pp.827-837
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    • 2012
  • The estimation of the rainfall quantile is of great importance in designing hydrologic structures. Conventionally, the rainfall quantile is estimated by univariate frequency analysis with an appropriate probability distribution. There is a limitation in which duration of rainfall is restrictive. To overcome this limitation, bivariate frequency analysis by using 3 copula models is performed in this study. Annual maximum rainfall events in 5 stations are used for frequency analysis and rainfall depth and duration are used as random variables. Gumbel (GUM), generalized logistic (GLO) distributions are applied for rainfall depth and generalized extreme value (GEV), GUM, GLO distributions are applied for rainfall duration. Copula models used in this study are Frank, Joe, and Gumbel-Hougaard models. Maximum pseudo-likelihood estimation method is used to estimate the parameter of copula, and the method of probability weighted moments is used to estimate the parameters of marginal distributions. Rainfall quantile from this procedure is compared with various marginal distributions and copula models. As a result, in change of marginal distribution, distribution of duration does not significantly affect on rainfall quantile. There are slight differences depending on the distribution of rainfall depth. In the case which the marginal distribution of rainfall depth is GUM, there is more significantly increasing along the return period than GLO. Comparing with rainfall quantiles from each copula model, Joe and Gumbel-Hougaard models show similar trend while Frank model shows rapidly increasing trend with increment of return period.

Growth and Yield of Direct Seeded Rice in Different Seeding Dates (벼 건답직파재배에서 파종기 이동에 따른 생육 및 수량)

  • 김상경;이승필;이외현;이광석;최부술
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.37 no.5
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    • pp.442-448
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    • 1992
  • In order to determine the critical seeding date in dry paddy field at southern plain area of Gyeongbug province, dry seeds of three different rice cultivars was sown April 25 to June 20 at 15 or 10-day intervals. The number of days from seeding to emergence decreased in late seeding date : from 32 days at April 25 to 7 days at June 10 sowing. The number of seedlings showed 121-154 plants per square meter were not much differed among the varieties and seeding dates. Culm length, panicle length and ripened grain ratio decreased in late seeding date, but number of panicles per square meter, 1,000 grain weight and spikelets number per panicle were similar among the seeding dates. The cumulative effective temperature(mean air temperature-15$^{\circ}C$) from emergence to heading was very constant having 655$\pm$9$^{\circ}C$ in Keomhobyeo, 771$\pm$9$^{\circ}C$ in Donghaebyeo and 801$\pm$3$^{\circ}C$ in Milyang 95, respectively. Grain yield of Dong Haebyeo seeded in June 20 and Milyang 95 seeded in June 10 were much lower compared with other seeding dates and increased green kernel in late seeding date of Donghaebyeo and Milyang 95.

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