• 제목/요약/키워드: Normal Distribution

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NORMAL FUZZY PROBABILITY FOR TRAPEZOIDAL FUZZY SETS

  • Kim, Changil;Yun, Yong Sik
    • East Asian mathematical journal
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    • 제29권3호
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    • pp.269-278
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    • 2013
  • A fuzzy set A defined on a probability space (${\Omega}$, $\mathfrak{F}$, P) is called a fuzzy event. Zadeh defines the probability of the fuzzy event A using the probability P. We define the normal fuzzy probability on $\mathbb{R}$ using the normal distribution. We calculate the normal fuzzy probability for generalized trapezoidal fuzzy sets and give some examples.

NORMAL FUZZY PROBABILITY FOR GENERALIZED QUADRATIC FUZZY SETS

  • Kim, Changil;Yun, Yong Sik
    • 충청수학회지
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    • 제25권2호
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    • pp.217-225
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    • 2012
  • A generalized quadratic fuzzy set is a generalization of a quadratic fuzzy number. Zadeh defines the probability of the fuzzy event using the probability. We define the normal fuzzy probability on $\mathbb{R}$ using the normal distribution. And we calculate the normal fuzzy probability for generalized quadratic fuzzy sets.

ON BAYESIAN ESTIMATION AND PROPERTIES OF THE MARGINAL DISTRIBUTION OF A TRUNCATED BIVARIATE t-DISTRIBUTION

  • KIM HEA-JUNG;KIM Ju SUNG
    • Journal of the Korean Statistical Society
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    • 제34권3호
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    • pp.245-261
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    • 2005
  • The marginal distribution of X is considered when (X, Y) has a truncated bivariate t-distribution. This paper mainly focuses on the marginal nontruncated distribution of X where Y is truncated below at its mean and its observations are not available. Several properties and applications of this distribution, including relationship with Azzalini's skew-normal distribution, are obtained. To circumvent inferential problem arises from adopting the frequentist's approach, a Bayesian method utilizing a data augmentation method is suggested. Illustrative examples demonstrate the performance of the method.

미세면 분포 함수 변형을 통한 고품질 실시간 금속 렌더링 (High-quality Realtime Rendering of Metallic Surface with Microfacet Distribution Function Deformation)

  • 강영민
    • 한국게임학회 논문지
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    • 제10권6호
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    • pp.169-178
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    • 2010
  • 본 논문은 실시간 응용 프로그램에서 사실적인 금속 재질을 렌더링하기 위한 효과적인 기법을 제안한다. 제안된 기법은 금속면의 미세한 흡집을 표현하기 위해 법선 벡터를 섭동(perturbation)하는 방법을 사용한다. 법선 벡터를 섭동하는 일반적인 방법은 범프(bump) 매핑이나 법선(normal) 매핑 등의 방법을 사용하는 것이다. 그러나 이러한 방식은 이방성 반사 특성을 갖는 표면에서는 사실적인 빛의 산란을 보이지 못한다. 금속 특유의 반사를 표현하기 위해서는 미세면 분포 함수를 이용하여 이방성 반사 특성을 모델링하는 것이 일반적이므로 일반적 법선 섭동만으로는 만족스런 결과를 얻지 못한다. 본 논문은 법선 벡터의 섭동과 함께 미세면 분포 함수를 변형하는 기법을 통해 매우 사실적인 금속면 재질 렌더링이 가능한 기법을 제안한 다. 제안된 기법은 쉽게 GPU 프로그램으로 구현되며, 실시간 환경에서 동작한다.

155mm 추진장약 포구속도의 확률분포 특성 연구 (A Study on Statistical Distribution of Muzzle Velocity of 155mm Propelling Charge)

  • 박성호;박노석;최병두;김재훈
    • 한국추진공학회:학술대회논문집
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    • 한국추진공학회 2009년도 제33회 추계학술대회논문집
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    • pp.339-343
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    • 2009
  • 본 논문에서 155mm 자주포 K9에 사용되는 추진장약 K676의 포구속도 확률분포에 관하여 분석하였다. K676 추진장약의 로트별 수락시험으로 얻어진 포구속도 자료를 분석하였으며 각 시험탄의 포구속도는 기준탄의 사격결과 값으로 보정하였다. 최근까지 수행된 사격시험으로 얻어진 모든 시험값에 대하여 적합도 검정을 하였으며, 정규분포, 2모수 와이블분포 및 3모수 와이블분포 중 정규분포가 가장 적합한 확률분포임을 확인하였고 와이블분포도 충분히 활용할 만하다. 변동계수로부터 추진장약의 양산능력이 균일하게 유지되고 있음을 알 수 있다.

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Unbounded Johnson 분포를 이용한 GARCH 수익률 모형의 적용 (GARCH Model with Conditional Return Distribution of Unbounded Johnson)

  • 정승현;오정준;김성곤
    • 응용통계연구
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    • 제25권1호
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    • pp.29-43
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    • 2012
  • 주식, 환율 등과 같은 금융자료의 수익률의 분포는 정규분포에 비해 꼬리가 두껍고, 좌우 비대칭성을 보인다. 조건부수익률이 정규분포를 따른다고 가정한 GARCH 모형을 이용하여 VaR을 추정하였을 때, 이러한 비정규성 때문에 적절한 추정이 이루어지지 않고, VaR을 초과하는 손실의 발생과정에 군집(clustering)현상이 발생하는 문제점이 있다. 이러한 문제를 해결하기 위해, 본 논문에서는 조건부수익률의 분포로 unbounded Johnson 분포를 이용한 GARCH 모형을 이용하여 VaR을 추정한다. 또한, 조건부수익률이 각각 정규분포, Student-t 분포를 따르는 GARCH 모형의 경우와 비교하였다. 초과손실 발생과정 자료를 이용하여 실패율검정과 군집성검정을 통해 조건부수익률 분포로 unbounded-Johnson 분포를 사용하는 방법의 타당성을 살펴보았다. Unbounded Johnson 분포가 조건부수익률 분포로 주어지는 GARCH 모형의 경우는 과소, 과대추정을 하지 않고, 군집현상 또한 발생하지 않아 적절한 추정을 하고 있음을 확인하였다.

수생태 독성자료의 정규성 분포 특성 확인을 통해 통계분석 시 분포 특성 적용에 대한 타당성 확인 연구 (The Validation Study of Normality Distribution of Aquatic Toxicity Data for Statistical Analysis)

  • 옥승엽;문효방;나진성
    • 한국환경보건학회지
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    • 제45권2호
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    • pp.192-202
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    • 2019
  • Objectives: According to the central limit theorem, the samples in population might be considered to follow normal distribution if a large number of samples are available. Once we assume that toxicity dataset follow normal distribution, we can treat and process data statistically to calculate genus or species mean value with standard deviation. However, little is known and only limited studies are conducted to investigate whether toxicity dataset follows normal distribution or not. Therefore, the purpose of study is to evaluate the generally accepted normality hypothesis of aquatic toxicity dataset Methods: We selected the 8 chemicals, which consist of 4 organic and 4 inorganic chemical compounds considering data availability for the development of species sensitivity distribution. Toxicity data were collected at the US EPA ECOTOX Knowledgebase by simple search with target chemicals. Toxicity data were re-arranged to a proper format based on the endpoint and test duration, where we conducted normality test according to the Shapiro-Wilk test. Also we investigated the degree of normality by simple log transformation of toxicity data Results: Despite of the central limit theorem, only one large dataset (n>25) follow normal distribution out of 25 large dataset. By log transforming, more 7 large dataset show normality. As a result of normality test on small dataset (n<25), log transformation of toxicity value generally increases normality. Both organic and inorganic chemicals show normality growth for 26 species and 30 species, respectively. Those 56 species shows normality growth by log transformation in the taxonomic groups such as amphibian (1), crustacean (21), fish (22), insect (5), rotifer (2), and worm (5). In contrast, mollusca shows normality decrease at 1 species out of 23 that originally show normality. Conclusions: The normality of large toxicity dataset was not always satisfactory to the central limit theorem. Normality of those data could be improved through log transformation. Therefore, care should be taken when using toxicity data to induce, for example, mean value for risk assessment.

Slip-Related Changes in Plantar Pressure Distribution, and Parameters for Early Detection of Slip Events

  • Choi, Seungyoung;Cho, Hyungpil;Kang, Boram;Lee, Dong Hun;Kim, Mi Jung;Jang, Seong Ho
    • Annals of Rehabilitation Medicine
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    • 제39권6호
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    • pp.897-904
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    • 2015
  • Objective To investigate differences in plantar pressure distribution between a normal gait and unpredictable slip events to predict the initiation of the slipping process. Methods Eleven male participants were enrolled. Subjects walked onto a wooden tile, and two layers of oily vinyl sheet were placed on the expected spot of the 4th step to induce a slip. An insole pressure-measuring system was used to monitor plantar pressure distribution. This system measured plantar pressure in four regions (the toes, metatarsal head, arch, and heel) for three events: the step during normal gait; the recovered step, when the subject recovered from a slip; and the uncorrected, harmful slipped step. Four variables were analyzed: peak pressure (PP), contact time (CT), the pressure-time integral (PTI), and the instant of peak pressure (IPP). Results The plantar pressure pattern in the heel was unique, as compared with other parts of the sole. In the heel, PP, CT, and PTI values were high in slipped and recovered steps compared with normal steps. The IPP differed markedly among the three steps. The IPPs in the heel for the three events were, in descending order (from latest to earliest), slipped, recovered, and normal steps, whereas in the other regions the order was normal, recovered, and slipped steps. Finally, the metatarsal head-to-heel IPP ratios for the normal, recovered, and slipped steps were $6.1{\pm}2.9$, $3.1{\pm}3.0$, and $2.2{\pm}2.5$, respectively. Conclusion A distinctive plantar pressure pattern in the heel might be useful for early detection of a slip event to prevent slip-related injuries.

On a Skew-t Distribution

  • Kim, Hea-Jung
    • Communications for Statistical Applications and Methods
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    • 제8권3호
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    • pp.867-873
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    • 2001
  • In this paper we propose a family of skew- f distributions. The family is derived by a scale mixtures of skew-normal distributions introduced by Azzalini (1985) and Henze (1986). The salient features of the family are mathematical tractability and strict inclusion of the normal law. Further it includes a shape parameter, to some extent, controls the index of skewness. Necessary theory involved in deriving the family of distributions is provided and main properties of the family are also studied.

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A Note on Parametric Bootstrap Model Selection

  • Lee, Kee-Won;Songyong Sim
    • Journal of the Korean Statistical Society
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    • 제27권4호
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    • pp.397-405
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    • 1998
  • We develop parametric bootstrap model selection criteria in an example to fit a random sample to either a general normal distribution or a normal distribution with prespecified mean. We apply the bootstrap methods in two ways; one considers the direct substitution of estimated parameter for the unknown parameter, and the other focuses on the bias correction. These bootstrap model selection criteria are compared with AIC. We illustrate that all the selection rules reduce to the one sample t-test, where the cutoff points converge to some certain points as the sample size increases.

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