• Title/Summary/Keyword: two parameter Weibull distribution

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Evaluation of wind power potential for selecting suitable wind turbine

  • Sukkiramathi, K.;Rajkumar, R.;Seshaiah, C.V.
    • Wind and Structures
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    • v.31 no.4
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    • pp.311-319
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    • 2020
  • India is a developing nation and heavily spends on the development of wind power plants to meet the national energy demand. The objective of this paper is to investigate wind power potential of Ennore site using wind data collected over a period of two years by three parameter Weibull distribution. The Weibull parameters are estimated using maximum likelihood, least square method and moment method and the accuracy is determined using R2 and root mean square error values. The site specific capacity factor is calculated by the mathematical model developed by three parameter Weibull distribution at different hub heights above the ground level. At last, the wind energy economic analysis is carried out using capacity factor at 30 m, 40 m and 50 m height for different wind turbine models. The analysis showed that the site has potential to install utility wind turbines to generate energy at the lowest cost per kilowatt-hour at height of 50 m. This research provides information of wind characteristics of potential sites and helps in selecting suitable wind turbine.

Tree Size Distribution Modelling: Moving from Complexity to Finite Mixture

  • Ogana, Friday Nwabueze;Chukwu, Onyekachi;Ajayi, Samuel
    • Journal of Forest and Environmental Science
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    • v.36 no.1
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    • pp.7-16
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    • 2020
  • Tree size distribution modelling is an integral part of forest management. Most distribution yield systems rely on some flexible probability models. In this study, a simple finite mixture of two components two-parameter Weibull distribution was compared with complex four-parameter distributions in terms of their fitness to predict tree size distribution of teak (Tectona grandis Linn f) plantations. Also, a system of equation was developed using Seemingly Unrelated Regression wherein the size distributions of the stand were predicted. Generalized beta, Johnson's SB, Logit-Logistic and generalized Weibull distributions were the four-parameter distributions considered. The Kolmogorov-Smirnov test and negative log-likelihood value were used to assess the distributions. The results show that the simple finite mixture outperformed the four-parameter distributions especially in stands that are bimodal and heavily skewed. Twelve models were developed in the system of equation-one for predicting mean diameter, seven for predicting percentiles and four for predicting the parameters of the finite mixture distribution. Predictions from the system of equation are reasonable and compare well with observed distributions of the stand. This simplified mixture would allow for wider application in distribution modelling and can also be integrated as component model in stand density management diagram.

Comparison of Parameter Estimation for Weibull Distribution

  • Wang, Fu-Kwun;J. Bert Keats;B. Y. Leu
    • International Journal of Reliability and Applications
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    • v.4 no.1
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    • pp.41-50
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    • 2003
  • This paper represents the first comprehensive comparison of the Newton-Raphson's method and Simple Iterative Procedure (SIP) in the maximum likelihood estimation of the two-parameter Weibull distribution. Computer simulation is employed to compare these two methods for multiply censored, singly censored data (Type I or Type Ⅱ censoring) and complete data. Results indicate the Newton-Raphson's with the Menon's estimated value, as an initial point remains the effective iterative procedure for estimating the parameters.

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Likelihood Function of Order Statistic with a Weibull Distribution (와이벌분포를 갖는 순위설계량의 우도함수)

  • Seo Nam-Su
    • Journal of the military operations research society of Korea
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    • v.9 no.2
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    • pp.39-43
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    • 1983
  • In this paper, we derive the likelihood function for the independent random order statistic whose underlying lifetime distribution is a two parameter Weibull form. For this purpose we first discuss the order statistic which represent a characteristic feature of most life and fatigue tests that they give rise to ordered observations. And, we describe the properties of the underlying Weibull model. The derived likelihood function is essential for establishing the statistical life test plans in the case of Weibull distribution using a likelihood ratio method.

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The Exponentiated Weibull-Geometric Distribution: Properties and Estimations

  • Chung, Younshik;Kang, Yongbeen
    • Communications for Statistical Applications and Methods
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    • v.21 no.2
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    • pp.147-160
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    • 2014
  • In this paper, we introduce the exponentiated Weibull-geometric (EWG) distribution which generalizes two-parameter exponentiated Weibull (EW) distribution introduced by Mudholkar et al. (1995). This proposed distribution is obtained by compounding the exponentiated Weibull with geometric distribution. We derive its cumulative distribution function (CDF), hazard function and the density of the order statistics and calculate expressions for its moments and the moments of the order statistics. The hazard function of the EWG distribution can be decreasing, increasing or bathtub-shaped among others. Also, we give expressions for the Renyi and Shannon entropies. The maximum likelihood estimation is obtained by using EM-algorithm (Dempster et al., 1977; McLachlan and Krishnan, 1997). We can obtain the Bayesian estimation by using Gibbs sampler with Metropolis-Hastings algorithm. Also, we give application with real data set to show the flexibility of the EWG distribution. Finally, summary and discussion are mentioned.

New approach to calculate Weibull parameters and comparison of wind potential of five cities of Pakistan

  • Ahmed Ali Rajput;Muhammad Daniyal;Muhammad Mustaqeem Zahid;Hasan Nafees;Misha Shafi;Zaheer Uddin
    • Advances in Energy Research
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    • v.8 no.2
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    • pp.95-110
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    • 2022
  • Wind energy can be utilized for the generation of electricity, due to significant wind potential at different parts of the world, some countries have already been generating of electricity through wind. Pakistan is still well behind and has not yet made any appreciable effort for the same. The objective of this work was to add some new strategies to calculate Weibull parameters and assess wind energy potential. A new approach calculates Weibull parameters; we also developed an alternate formula to calculate shape parameters instead of the gamma function. We obtained k (shape parameter) and c (scale parameter) for two-parameter Weibull distribution using five statistical methods for five different cities in Pakistan. Maximum likelihood method, Modified Maximum likelihood Method, Method of Moment, Energy Pattern Method, Empirical Method, and have been to calculate and differentiate the values of (shape parameter) k and (scale parameter) c. The performance of these five methods is estimated using the Goodness-of-Fit Test, including root mean square error, mean absolute bias error, mean absolute percentage error, and chi-square error. The daily 10-minute average values of wind speed data (obtained from energydata.info) of different cities of Pakistan for the year 2016 are used to estimate the Weibull parameters. The study finds that Hyderabad city has the largest wind potential than Karachi, Quetta, Lahore, and Peshawar. Hyderabad and Karachi are two possible sites where wind turbines can produce reasonable electricity.

Application of the Weibull-Poisson long-term survival model

  • Vigas, Valdemiro Piedade;Mazucheli, Josmar;Louzada, Francisco
    • Communications for Statistical Applications and Methods
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    • v.24 no.4
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    • pp.325-337
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    • 2017
  • In this paper, we proposed a new long-term lifetime distribution with four parameters inserted in a risk competitive scenario with decreasing, increasing and unimodal hazard rate functions, namely the Weibull-Poisson long-term distribution. This new distribution arises from a scenario of competitive latent risk, in which the lifetime associated to the particular risk is not observable, and where only the minimum lifetime value among all risks is noticed in a long-term context. However, it can also be used in any other situation as long as it fits the data well. The Weibull-Poisson long-term distribution is presented as a particular case for the new exponential-Poisson long-term distribution and Weibull long-term distribution. The properties of the proposed distribution were discussed, including its probability density, survival and hazard functions and explicit algebraic formulas for its order statistics. Assuming censored data, we considered the maximum likelihood approach for parameter estimation. For different parameter settings, sample sizes, and censoring percentages various simulation studies were performed to study the mean square error of the maximum likelihood estimative, and compare the performance of the model proposed with the particular cases. The selection criteria Akaike information criterion, Bayesian information criterion, and likelihood ratio test were used for the model selection. The relevance of the approach was illustrated on two real datasets of where the new model was compared with its particular cases observing its potential and competitiveness.

A Study of Test for the Reliability of Weibull Distribution Using Hybrid Censoring (혼합중도중단에 의한 Weibull분포의 신뢰도에 관한 검정의 연구)

  • Yeom, Jun-Geun;Ham, Hyeong-Beom
    • Journal of Korean Society for Quality Management
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    • v.20 no.1
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    • pp.48-58
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    • 1992
  • This paper deals with a test procedures on reliablity using hybrid censoring when failure time follows two parameter Weibull distribution. In each case of single and two stage test with hybrid censoring, we construct a operating characteristic curve, and then obtain the censoring number and sample size which the producer's risk and the consumer's risk are both satisfied. This study suggests to determine the expected waiting time at a decision.

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Novel estimation based on a minimum distance under the progressive Type-II censoring scheme

  • Young Eun Jeon;Suk-Bok Kang;Jung-In Seo
    • Communications for Statistical Applications and Methods
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    • v.30 no.4
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    • pp.411-421
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    • 2023
  • This paper provides a new estimation equation based on the concept of a minimum distance between the empirical and theoretical distribution functions under the most widely used progressive Type-II censoring scheme. For illustrative purposes, simulated and real datasets from a three-parameter Weibull distribution are analyzed. For comparison, the most popular estimation methods, the maximum likelihood and maximum product of spacings estimation methods, are developed together. In the analysis of simulated datasets, the excellence of the provided estimation method is demonstrated through the degree of the estimation failure of the likelihood-based method, and its validity is demonstrated through the mean squared errors and biases of the estimators obtained from the provided estimation equation. In the analysis of the real dataset, two types of goodness-of-fit tests are performed on whether the observed dataset has the three-parameter Weibull distribution under the progressive Type-II censoring scheme, through which the performance of the new estimation equation provided is examined.

Probabilistic Characteristics of Fatigue Behavior Parameter of Paris-Erdogan Law in Mg-Al-Zn Alloy (Mg-Al-Zn 합금의 Paris-Erdogan 법칙에 따른 피로거동 파라미터의 확률론적 특성)

  • Choi, Seon-Soon
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.35 no.4
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    • pp.375-381
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    • 2011
  • The primary aim of this study is to investigate the probabilistic characteristics of the fatigue parameters that describe the fatigue crack growth behavior in magnesium alloy. Statistical fatigue crack propagation experiments have been performed on rolled AZ31 magnesium alloy CT specimens with different specimen thickness, load ratio, and maximum load at ambient temperature in a laboratory. Using the statistical fatigue data obtained from these experiments, the goodness-of-fit of the probability distribution of the fatigue behavior parameters is evaluated in this study by performing statistical analyses. The crack growth rate coefficient is a fatigue parameter having a very large COV(Coefficient of Variation), but the variation of a crack growth rate exponent is not substantial. It is considered that a crack growth rate exponent can be a material constant. It is also found that the best fit probability distribution of the parameters such as the crack growth rate coefficient and crack growth rate exponent for a magnesium alloy is a three-parameter Weibull distribution, and two-parameter Weibull distribution is a good distribution only for the crack growth rate coefficient.