• Title/Summary/Keyword: Bivariate Measures

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The Bivariate Kumaraswamy Weibull regression model: a complete classical and Bayesian analysis

  • Fachini-Gomes, Juliana B.;Ortega, Edwin M.M.;Cordeiro, Gauss M.;Suzuki, Adriano K.
    • Communications for Statistical Applications and Methods
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    • v.25 no.5
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    • pp.523-544
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    • 2018
  • Bivariate distributions play a fundamental role in survival and reliability studies. We consider a regression model for bivariate survival times under right-censored based on the bivariate Kumaraswamy Weibull (Cordeiro et al., Journal of the Franklin Institute, 347, 1399-1429, 2010) distribution to model the dependence of bivariate survival data. We describe some structural properties of the marginal distributions. The method of maximum likelihood and a Bayesian procedure are adopted to estimate the model parameters. We use diagnostic measures based on the local influence and Bayesian case influence diagnostics to detect influential observations in the new model. We also show that the estimates in the bivariate Kumaraswamy Weibull regression model are robust to deal with the presence of outliers in the data. In addition, we use some measures of goodness-of-fit to evaluate the bivariate Kumaraswamy Weibull regression model. The methodology is illustrated by means of a real lifetime data set for kidney patients.

BIVARIATE DYNAMIC CUMULATIVE RESIDUAL TSALLIS ENTROPY

  • SATI, MADAN MOHAN;SINGH, HARINDER
    • Journal of applied mathematics & informatics
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    • v.35 no.1_2
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    • pp.45-58
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    • 2017
  • Recently, Sati and Gupta (2015) proposed two measures of uncertainty based on non-extensive entropy, called the dynamic cumulative residual Tsallis entropy (DCRTE) and the empirical cumulative Tsallis entropy. In the present paper, we extend the definition of DCRTE into the bivariate setup and study its properties in the context of reliability theory. We also define a new class of life distributions based on bivariate DCRTE.

Application of the BMORE Plot to Analyze Simulation Output Data with Bivariate Performance Measures (이변량 성과척도를 가지는 시뮬레이션 결과 분석을 위한 BMORE 도표의 활용)

  • Lee, Mi Lim;Lee, Jinpyo;Park, Minjae
    • Journal of the Korea Society for Simulation
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    • v.29 no.2
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    • pp.83-93
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    • 2020
  • Bivariate measure of risk and error(BMORE) plot is originally designed to depict bivariate output data and related statistics obtained from a stochastic simulation such as sample mean, median, outliers, and a boundary of a certain percentile of simulation data. When compared to the static numbers, the plot has a big advantage in visualization that enables scholars and practitioners to understand the potential variability and risk in the simulation data. In this study, beyond just the construction of the plot to depict the variability of a certain system, we add a chance constraint to the plot and apply it for decision making such as checking the feasibility of systems, comparing performances of the systems on statistical background, and also analyzing the sensitivity of the problem parameters. In order to demonstrate an application of the plot, we employ an inventory management problem as an example. However, the techniques and algorithms suggested in this paper can be applied to any other problems comparing systems on bivariate performance measures with simulation/experiment results.

Bivariate Failure Modeling

  • Baik, Jai-Wook;Jo, Jin-Nam
    • Proceedings of the Korean Society for Quality Management Conference
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    • 2006.04a
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    • pp.493-495
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    • 2006
  • People frequently discuss equipment behavior in terms of time(age) and usage(mileage). Common examples are automobiles in which time and usageare usually included in discussion of longevity. In this paper a structured examination of bivariate measures of equipment utilization is performed and some useful model forms are developed and evaluated.

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Aspects of Dependence in Lomax Distribution

  • Asadian, N.;Amini, M.;Bozorgnia, A.
    • Communications for Statistical Applications and Methods
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    • v.15 no.2
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    • pp.193-204
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    • 2008
  • In this paper we study some positive dependence concepts, introduced by Caperaa and Genest (1990) and Shaked (1977b), for bivariate lomax distribution. In particular, we obtain some measures of association for this distribution and derive the tail-dependence coefficients by using copula function. We also compare Spearman's $\rho_s$ with Kendall's $\tau$ for bivariate lomax distribution.

A Bootstrap Test of Independence for an Absolutely Continuous Bivariate Exponential Model

  • Lee, In Suk;Kim, Dal Ho;Cho, Jang Sik
    • Journal of Korean Society for Quality Management
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    • v.24 no.2
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    • pp.77-86
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    • 1996
  • In this paper, we consider the problem of testing independence in the absolutely continuous bivariate exponential distribution of Block and Basu(1974). We construct a bootstrap procedure for testing zero and non-zero values of the parameter ${\lambda}_3$ which measures the degree of dependence and compare the power of the bootstrap test with likelihood ratio test(LRT) by Gupta et al.(1984) and the test based on maximum likelihood estimator(MLE) $\hat{{\lambda}}_3$ by Hanagal and Kale(1991) for small and moderate sample sizes.

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Consideration of human disturbance to enhance avian species richness in urban ecosystem (도시생태계 내 조류 종풍부도 증진을 위한 인간영향 및 교란가능성의 반영)

  • Kim, Yoon-Jung
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.24 no.5
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    • pp.25-34
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    • 2021
  • Increase in avian species richness is one of the important issues of urban biodiversity policies, since it can promote diverse ecosystem services such as seed dispersal, education, and pollination. However, though human disturbance can significantly affect avian species richness, there are limited studies on the way to reflect the dynamics of floating population. Therefore, this study analyzed the spatial relationship between avian species richness, floating population, and vegetation cover using telecommunications information to identify the areas that requiring targeted monitoring and restoration action. Bivariate Local Moran's I was applied to identify LISA cluster map that showing representative biotopes, which reflect significant spatial relationship between species richness and population distribution. Edge density and distribution of ndvi were identified for evaluating relative adequacy of selected biotopes to strengthen the robust biodiversity network. This study offers insight to consider human disturbance in spatial context using innovative big data to increase the effectiveness of urban biodiversity measures.

Bivariate long range dependent time series forecasting using deep learning (딥러닝을 이용한 이변량 장기종속시계열 예측)

  • Kim, Jiyoung;Baek, Changryong
    • The Korean Journal of Applied Statistics
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    • v.32 no.1
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    • pp.69-81
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    • 2019
  • We consider bivariate long range dependent (LRD) time series forecasting using a deep learning method. A long short-term memory (LSTM) network well-suited to time series data is applied to forecast bivariate time series; in addition, we compare the forecasting performance with bivariate fractional autoregressive integrated moving average (FARIMA) models. Out-of-sample forecasting errors are compared with various performance measures for functional MRI (fMRI) data and daily realized volatility data. The results show a subtle difference in the predicted values of the FIVARMA model and VARFIMA model. LSTM is computationally demanding due to hyper-parameter selection, but is more stable and the forecasting performance is competitively good to that of parametric long range dependent time series models.

A PARTIAL ORDERING OF WEAK POSITIVE QUADRANT DEPENDENCE

  • Kim, Tae-Sung;Lee, Young-Ro
    • Communications of the Korean Mathematical Society
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    • v.11 no.4
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    • pp.1105-1116
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    • 1996
  • A partial ordering is developed among weakly positive quadrant dependent (WPQD) bivariate random vectors. This permits us to measure the degree of WPQD-ness and to compare pairs of WPQD random vectors. Some properties and closures under certain statistical operations are derived. An application is made to measures of dependence such as Kendall's $\tau$ and Spearman's $\rho$.

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Assessment of Hydrologic Risk of Extreme Drought According to RCP Climate Change Scenarios Using Bivariate Frequency Analysis (이변량 빈도분석을 이용한 RCP 기후변화 시나리오에 따른 극한가뭄의 수문학적 위험도 평가)

  • Park, Ji Yeon;Kim, Ji Eun;Lee, Joo-Heon;Kim, Tae-Woong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.39 no.5
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    • pp.561-568
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    • 2019
  • Recently, Korea has suffered from severe droughts due to climate change. Therefore, we need to pay attention to the change of drought risk to develop appropriate drought mitigation measures. In this study, we investigated the changes of hydrologic risk of extreme drought using the current observed data and the projected data according to the RCP 4.5 and 8.5 climate change scenarios. The bivariate frequency analysis was performed for the paired data of drought duration and severity extracted by the threshold level method and by eliminating pooling and minor droughts. Based on the hydrologic risk of extreme drought events Jeonbuk showed the highest risk and increased by 51 % than the past for the RCP 4.5 scenario, while Gangwon showed the highest risk and increased by 47 % than the past for the RCP 8.5 scenario.