• Title/Summary/Keyword: Exponential and Weibull Distribution Function

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Some Exponentiated Distributions

  • Ali, M. Masoom;Pal, Manisha;Woo, Jung-Soo
    • Communications for Statistical Applications and Methods
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    • v.14 no.1
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    • pp.93-109
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    • 2007
  • In this paper we study a number of new exponentiated distributions. The survival function, failure rate and moments of the distributions have been derived using certain special functions. The behavior of the failure rate has also been studied.

Application of Weibull Distribution Function to Analysis of Breakthrough Curves from Push Pull Tracer Test

  • Hyun-Tae, Hwang;Lee, Kang-Kun
    • Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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    • 2003.04a
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    • pp.217-220
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    • 2003
  • In the case of the remediation studies, push pull test is a more time and cost effective mettled than multi-well tracer test. It also gives Just as much or more information than the traditionally used methods. But the data analysis for the hydraulic parameters, there have been some defections such as underestimation of dispersivity, requirement for effective porosity, and calculation of recovery of center of mass to estimate linear velocity. In this research, Weibull distribution function is proposed to estimate the center of mass of breakthrough curve for Push pull test. The hydraulic parameter estimation using Weibull function showed more exact values of center of mass than those of exponential regression for field test data.

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Inverted exponentiated Weibull distribution with applications to lifetime data

  • Lee, Seunghyung;Noh, Yunhwan;Chung, Younshik
    • Communications for Statistical Applications and Methods
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    • v.24 no.3
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    • pp.227-240
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    • 2017
  • In this paper, we introduce the inverted exponentiated Weibull (IEW) distribution which contains exponentiated inverted Weibull distribution, inverse Weibull (IW) distribution, and inverted exponentiated distribution as submodels. The proposed distribution is obtained by the inverse form of the exponentiated Weibull distribution. In particular, we explain that the proposed distribution can be interpreted by Marshall and Olkin's book (Lifetime Distributions: Structure of Non-parametric, Semiparametric, and Parametric Families, 2007, Springer) idea. We derive the cumulative distribution function and hazard function and calculate expression for its moment. The hazard function of the IEW distribution can be decreasing, increasing or bathtub-shaped. The maximum likelihood estimation (MLE) is obtained. Then we show the existence and uniqueness of MLE. We can also obtain the Bayesian estimation by using the Gibbs sampler with the Metropolis-Hastings algorithm. We also give applications with a simulated data set and two real data set to show the flexibility of the IEW distribution. Finally, conclusions are mentioned.

Simulation of Run-Length and Run-Sum of Daily Rainfall and Streamflow (일수문량의 RUN-LENGTH 및 RUN-SUM의 SIMULATION)

  • 이순택;지홍기
    • Water for future
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    • v.10 no.1
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    • pp.79-94
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    • 1977
  • This study is aimed at the establishment and examination of stochastic model to simulate Run-length and Run-sum of daily rainfall and streamflow. In the analysis, daily rainfall records in major cities (Seoul, Kangnung, Taegu, Kwangju, Busan, and Cheju) and daily streamflow records of Major rivers (Han, Nakdong and Geum River) were used. Also, the fitness of daily rainfall and streamflow to Weibull and one parameter exponential distribution was tested by Chi-square and Kolmogorov-Smirnov test, from which it was found that daily rainfall and streamflow generally fit well to exponential type distribution function. The Run-length and Run-sum were simulated by the Weibull Model (WBL Model), one parameter exponential model (EXP-1 Model) based on the Nonte Carlo technique. In this result, Run-length of rainfall was fitted for one parameter exponential model and Run-length of streamflow was fitted for Weibull model. And Run-sum of rainfall and streamflow were fit comparatively for regression model. Hereby, statistical charactristics of Simulation data were sinilar to historical data.

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Field Reliability Analysis of S-Bond of AF Track Circuit for Automatic Train Control System (자동열차제어장치 AF궤도회로 S-BOND의 사용신뢰도 분석)

  • Choi, Kyu-Hyoung;Rho, Young-Whan
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.2
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    • pp.308-313
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    • 2009
  • This paper presents a reliability analysis of S-bonds for AF track circuits, which detect train movement and transmit a speed control signal to the train. Field survey shows that S-bonds are exposed to very large vibrations transferred from rail, and suffer from frequent failures when they were installed on ballasted track. We collected the time-to-failure data of S-bonds from the maintenance field of Seoul metro line 2, and made a parametric approach to estimate the statistical distribution that fits the time-to-failure data. The analysis shows that S-bonds have time-to-failure characteristics described by Weibull distribution. The estimated shape parameter of Weibull distribution is 1.1, which means the distribution has constant failure rate characteristics like exponential distribution. The reliability function, hazard function, percentiles and mean lifetime are derived for maintenance support.

A Study on the Mathematical Modeling of Failure Rates Estimation for Asset Management of the Power Transformer (전력용변압기의 자산관리를 위한 고장률 추정기법의 수학적 모델링에 관한 연구)

  • MOU, SHUAILONG;Jang, Kyung-Wook;Baek, Seung-Myung;Shon, Jin-Geun
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.66 no.1
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    • pp.33-37
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    • 2017
  • This paper describes the modeling of the failure rate estimation technique for applying the asset management technique to electric power facilities. There are many modeling techniques to estimate the failure rate. In this paper, the characteristics of the normal distribution, exponential distribution, weibull distribution, and piecewise linear functions are discussed. When evaluating reliability, the evaluation may be less meaningful if the sample data is insufficient. Therefore, Weibull distribution and piecewise linear function are adopted as the most suitable functions for estimating the failure rate of power facilities and the resulting failure rate function is derived.

Sigmoid Curve Model for Software Test-Effort Estimation (소프트웨어 시험 노력 추정 시그모이드 모델)

  • Lee, Sang-Un
    • The KIPS Transactions:PartD
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    • v.11D no.4
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    • pp.885-892
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    • 2004
  • Weibull distribution Iincluding Rayleigh and Exponential distribution is a typical model to estimate the effort distribution which is committed to the software testing phase. This model does not represent standpoint that many efforts are committed actually at the test beginning point. Moreover, it does not properly represent the various distribution form of actual test effort. To solve these problems, this paper proposes the Sigmoid model. The sigmoid function to be applicable in neural network transformed into the function which properly represents the test effort of software in the model. The model was verified to the six test effort data which were got from actual software projects which have various distribution form and verified the suitability. The Sigmoid model nay be selected by the alternative of Weibull model to estimate software test effort because it is superior than the Weibull model.

Estimation of sewer deterioration by Weibull distribution function (와이블 분포함수를 이용한 하수관로 노후도 추정)

  • Kang, Byongjun;Yoo, Soonyu;Park, Kyoohong
    • Journal of Korean Society of Water and Wastewater
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    • v.34 no.4
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    • pp.251-258
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    • 2020
  • Sewer deterioration models are needed to forecast the remaining life expectancy of sewer networks by assessing their conditions. In this study, the serious defect (or condition state 3) occurrence probability, at which sewer rehabilitation program should be implemented, was evaluated using four probability distribution functions such as normal, lognormal, exponential, and Weibull distribution. A sample of 252 km of CCTV-inspected sewer pipe data in city Z was collected in the first place. Then the effective data (284 sewer sections of 8.15 km) with reliable information were extracted and classified into 3 groups considering the sub-catchment area, sewer material, and sewer pipe size. Anderson-Darling test was conducted to select the most fitted probability distribution of sewer defect occurrence as Weibull distribution. The shape parameters (β) and scale parameters (η) of Weibull distribution were estimated from the data set of 3 classified groups, including standard errors, 95% confidence intervals, and log-likelihood values. The plot of probability density function and cumulative distribution function were obtained using the estimated parameter values, which could be used to indicate the quantitative level of risk on occurrence of CS3. It was estimated that sewer data group 1, group 2, and group 3 has CS3 occurrence probability exceeding 50% at 13th-year, 11th-year, and 16th-year after the installation, respectively. For every data groups, the time exceeding the CS3 occurrence probability of 90% was also predicted to be 27th- to 30th-year after the installation.

Estimation for the Exponentiated Exponential Distribution Based on Multiply Type-II Censored Samples

  • Kang Suk-Bok;Park Sun-Mi
    • Communications for Statistical Applications and Methods
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    • v.12 no.3
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    • pp.643-652
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    • 2005
  • It has been known that the exponentiated exponential distribution can be used as a possible alternative to the gamma distribution or the Weibull distribution in many situations. But the maximum likelihood method does not admit explicit solutions when the sample is multiply censored. So we derive the approximate maximum likelihood estimators for the location and scale parameters in the exponentiated exponential distribution that are explicit function of order statistics. We also compare the proposed estimators in the sense of the mean squared error for various censored samples.

Extraction of Time-varying Failure Rate for Power Distribution System Equipment (배전계통 설비의 시변 고장률 추출)

  • Moon, Jong-Fil;Lee, Hee-Tae;Kim, Jae-Chul;Park, Chang-Ho
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.54 no.11
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    • pp.548-556
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    • 2005
  • Reliability evaluation of power distribution system is very important to both power utilities and customers. It present the probabilistic number and duration of interruption such as failure rate, SATDI, SAIFI, and CAIDI. However, it has a fatal weakness at reliability index because of accuracy of failure rate. In this paper, the Time-varying Failure Rate(TFR) of power distribution system equipment is extracted from the recorded failure data of KEPCO(Korea Electric Power Corporation) in Korea. For TFR extraction, it is used that the fault data accumulated by KEPCO during 10 years. The TFR is approximated to bathtub curve using the exponential(random failure) and Weibull(aging failure) distribution function. In addition, Kaplan-Meier estimation is applied to TFR extraction because of incomplete failure data of KEPCO. Finally, Probability plot and regression analysis is applied. It is presented that the extracted TFR is more effective and useful than Mean Failure Rate(MfR) through the comparison between TFR and MFR