• Title/Summary/Keyword: different method of estimation and applications

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A new extension of Lindley distribution: modified validation test, characterizations and different methods of estimation

  • Ibrahim, Mohamed;Yadav, Abhimanyu Singh;Yousof, Haitham M.;Goual, Hafida;Hamedani, G.G.
    • Communications for Statistical Applications and Methods
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    • 제26권5호
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    • pp.473-495
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    • 2019
  • In this paper, a new extension of Lindley distribution has been introduced. Certain characterizations based on truncated moments, hazard and reverse hazard function, conditional expectation of the proposed distribution are presented. Besides, these characterizations, other statistical/mathematical properties of the proposed model are also discussed. The estimation of the parameters is performed through different classical methods of estimation. Bayes estimation is computed under gamma informative prior under the squared error loss function. The performances of all estimation methods are studied via Monte Carlo simulations in mean square error sense. The potential of the proposed model is analyzed through two data sets. A modified goodness-of-fit test using the Nikulin-Rao-Robson statistic test is investigated via two examples and is observed that the new extension might be used as an alternative lifetime model.

Analysis of Real-Time Estimation Method Based on Hidden Markov Models for Battery System States of Health

  • Piao, Changhao;Li, Zuncheng;Lu, Sheng;Jin, Zhekui;Cho, Chongdu
    • Journal of Power Electronics
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    • 제16권1호
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    • pp.217-226
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    • 2016
  • A new method is proposed based on a hidden Markov model (HMM) to estimate and analyze battery states of health. Battery system health states are defined according to the relationship between internal resistance and lifetime of cells. The source data (terminal voltages and currents) can be obtained from vehicular battery models. A characteristic value extraction method is proposed for HMM. A recognition framework and testing datasets are built to test the estimation rates of different states. Test results show that the estimation rates achieved based on this method are above 90% under single conditions. The method achieves the same results under hybrid conditions. We can also use the HMMs that correspond to hybrid conditions to estimate the states under a single condition. Therefore, this method can achieve the purpose of the study in estimating battery life states. Only voltage and current are used in this method, thereby establishing its simplicity compared with other methods. The batteries can also be tested online, and the method can be used for online prediction.

The exponential generalized log-logistic model: Bagdonavičius-Nikulin test for validation and non-Bayesian estimation methods

  • Ibrahim, Mohamed;Aidi, Khaoula;Alid, Mir Masoom;Yousof, Haitham M.
    • Communications for Statistical Applications and Methods
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    • 제29권1호
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    • pp.1-25
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    • 2022
  • A modified Bagdonavičius-Nikulin chi-square goodness-of-fit is defined and studied. The lymphoma data is analyzed using the modified goodness-of-fit test statistic. Different non-Bayesian estimation methods under complete samples schemes are considered, discussed and compared such as the maximum likelihood least square estimation method, the Cramer-von Mises estimation method, the weighted least square estimation method, the left tail-Anderson Darling estimation method and the right tail Anderson Darling estimation method. Numerical simulation studies are performed for comparing these estimation methods. The potentiality of the new model is illustrated using three real data sets and compared with many other well-known generalizations.

움직임 보상 보간 프레임에 대한 프레임 적응적 왜곡 예측 기법 (Frame-Adaptive Distortion Estimation for Motion Compensated Interpolated Frame)

  • 김진수
    • 한국콘텐츠학회논문지
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    • 제12권3호
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    • pp.1-8
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    • 2012
  • 비디오 프레임 율 증가 변환은 가전 분야에서 매우 다양한 응용으로 인해 매우 많은 관심을 받아 오고 있다. 대 부분의 진보된 FRUC 알고리즘은 보간된 프레임들의 움직임 벡터장을 결정하는 움직임 보간 기술을 사용하고 있다. 그러나 몇 개의 응용 분야에서는 움직임 보상 보간 프레임이 얼마나 잘 복원되었는지에 대한 정보를 필요로 한다. 이와 같은 목적을 위해 본 논문에서는 프레임 기반의 적응적 예측에 기초한 움직임 보상 보간 프레임의 왜곡 예측 기법을 제안한다. 제안된 기법은 대칭형 움직임 탐색 및 보상 보간 기법에 적용되며, 세 가지 다른 예측 기법 즉, 순방향, 역방향 그리고 적응적 양방향 예측 기법으로 분석된다. 모의 실험을 통하여 제안된 적응적 양방향 왜곡 예측 방식이 다른 두 방식에 비해 성능이 우수함을 보인다.

Comparison of different estimators of P(Y

  • Hassan, Marwa KH.
    • International Journal of Reliability and Applications
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    • 제18권2호
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    • pp.83-98
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    • 2017
  • Stress-strength reliability problems arise frequently in applied statistics and related fields. In the context of reliability, the stress-strength model describes the life of a component, which has a random strength X and is subjected to random stress Y. The component fails at the instant that the stress applied to it exceeds the strength and the component will function satisfactorily whenever X > Y. The problem of estimation the reliability parameter in a stress-strength model R = P[Y < X], when X and Y are two independent two-parameter Lindley random variables is considered in this paper. The maximum likelihood estimator (MLE) and Bayes estimator of R are obtained. Also, different confidence intervals of R are obtained. Simulation study is performed to compare the different proposed estimation methods. Example in real data is used as practical application of the proposed procedure.

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A computational note on maximum likelihood estimation in random effects panel probit model

  • Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
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    • 제26권3호
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    • pp.315-323
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    • 2019
  • Panel data sets have recently been developed in various areas, and many recent studies have analyzed panel, or longitudinal data sets. Often a dichotomous dependent variable occur in survival analysis, biomedical and epidemiological studies that is analyzed by a generalized linear mixed effects model (GLMM). The most common estimation method for the binary panel data may be the maximum likelihood (ML). Many statistical packages provide ML estimates; however, the estimates are computed from numerically approximated likelihood function. For instance, R packages, pglm (Croissant, 2017) approximate the likelihood function by the Gauss-Hermite quadratures, while Rchoice (Sarrias, Journal of Statistical Software, 74, 1-31, 2016) use a Monte Carlo integration method for the approximation. As a result, it can be observed that different packages give different results because of different numerical computation methods. In this note, we discuss the pros and cons of numerical methods compared with the exact computation method.

Variance estimation of a double expanded estimator for two-phase sampling

  • Mingue Park
    • Communications for Statistical Applications and Methods
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    • 제30권4호
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    • pp.403-410
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    • 2023
  • Two-Phase sampling, which was first introduced by Neyman (1938), has various applications in different forms. Variance estimation for two-phase sampling has been an important research topic because conventional variance estimators used in most softwares are not working. In this paper, we considered a variance estimation for two-phase sampling in which stratified two-stage cluster sampling designs are used in both phases. By defining a conditionally unbiased estimator of an approximate variance estimator, which is calculable when all elements in the first phase sample are observed, we propose an explicit form of variance estimator of the double expanded estimator for a two-phase sample. A small simulation study shows the proposed variance estimator has a negligible bias with small variance. The suggested variance estimator is also applicable to other linear estimators of the population total or mean if appropriate residuals are defined.

Voltage Sag and Swell Estimation Using ANFIS for Power System Applications

  • Malmurugan, N.;Gopal, Devarajan;Lho, Young Hwan
    • 한국철도학회논문집
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    • 제16권4호
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    • pp.272-277
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    • 2013
  • Power quality is a term that is now extensively used in power systems applications, and in this context the voltage, current, and phase angle are discussed widely. In particular, different algorithms that are capable of detecting the voltage sag and swell information in a real time environment have been proposed and developed. Voltage sag and swell play an important role in determining the stability, quality, and operation of a power system. This paper presents ANFIS (Adaptive Network based Fuzzy Inference System) models with different membership functions to build the voltage shape with the knowledge of known system parameters, and detect voltage sag and swell accurately. The performance of each method has been compared with each other/other methods to determine the effectiveness of the different models, and the results are presented.

2차 스마트 센서의 센싱능력 평가기법 개발 (Development of Estimation Method of Sensing Ability of $2^{nd}$ Smart Sensor)

  • 황성연;홍동표;강희용;박준홍
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1997년도 추계학술대회 논문집
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    • pp.209-213
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    • 1997
  • This paper deals with sensing ability of $2^{nd}$ smart sensor that has a sensing ability of distinguish materials. We have developed new signal processing method that have distinguish different materials. We made the $2^{nd}$ smart sensor for experiment. The second type of smart sensor is HH type. We have developed a new signal processing method that can distinguish among different materials. The estimation method (RSAIIn dex) is developed for $2^{nd}$ smart sensor(HH smart sensor). Experiment and analysis are executed for estimation the new method. We estimated sensing ability of $2^{nd}$ smart sensor with RsA, method. Sensing Ability of the $2^{nd}$ smart sensor were evaluated relatively through a new RsAl method. According to frequency changing, influences of the $2^{nd}$ smart sensor are evaluated through a new recognition index RSAI. Applications of this method are for finding abnormal conditions of objects (automanufacturing), feeling of objects (medical product), robotics, safety diagnosis of structure, etc.

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Spatial Data Analysis using the Kriging Method

  • Jang, Jihui;Hong, Taekyong;NamKung, Pyong
    • Communications for Statistical Applications and Methods
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    • 제10권2호
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    • pp.423-432
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    • 2003
  • The data observed at different positions are called the estimate of interested variable at new observation point on the Kriging utilize the space estimate technique, in which case there is correlation spatially. In this paper we provide the estimate for Variogram and Kriging methods as a field of kriging theory and dealt with actually measured data. And at the same time we forecast the amount of ozone that was not measured at this point by Kriging method and compared Ordinary Kriging method with Inverse Distance Kriging method.