• Journal of the Society of Disaster Information
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• v.17 no.2
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• pp.319-328
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• 2021

Purpose: Recently, a large social disaster has called for the need to diagnose social disaster safety, and the Ministry of Public Administration and Security calculates and publishes regional safety ratings such as regional safety index and national safety diagnosis every year. The existing safety diagnosis system uses equal intervals or normal distribution to grade risk maps in a uniform manner. Method: However, the equidistant technique can objectively analyze risk ratings, but there is a limit to classifying risk ratings when the distribution is skewed to one side, and the z-score technique has a problem of losing credibility if the population does not follow a normal distribution. Because the distribution of statistical data varies from indicator to indicator, the most appropriate rating should be applied for each data distribution. Result: Therefore, in this paper, we analyze the data of disaster indicators and present a comparison and suitable method for traditional equidistant and natural brake techniques to proceed with optimized grading for each indicator. Conclusion: As a result, three of the six new indicators were applied differently from conventional grading techniques

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.237-248
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• 2009

The probability of default on the credit evaluation study is represented as a linear combination of two distributions of default and non-default, and the distribution of the probability of default are generally known in most cases. Except the well-known Kolmogorov-Smirnov statistic for testing the identity of two distribution, Kuiper, Cramer-Von Mises, Anderson-Darling, and Watson test statistics are introduced in this work. Under the assumption that the population distribution is known, modified Cramer-Von Mises, Anderson-Darling, and Watson statistics are proposed. Based on score data generated from various probability density functions of the probability of default, the modified test statistics are discussed and compared.

• The Journal of Industrial Distribution & Business
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• v.13 no.9
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• pp.1-9
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• 2022

Purpose: This study evaluates the ability to improve the economic welfare of rural communities in Indonesia by using the inequality measures of the distribution of information between leaders and their people as a variable that weakens the capacity of increasing the welfare. Research Design, Data, and Methodology: The research designed by developing an instrument using data validity and reliability testing. Before, primary data collected through interviews, questionnaires, observation, and documentation on the selected respondents. Then, the research method used is mixed methods research, in which quantitative and qualitative methods combined. Result: The finding from this study is that there is an inequality measure in the form of a high gap between the score of information distribution obtained by the village government compared to the score of the community, which has led to the welfare of the village which is still at a moderate level and not ready to become a prosperous society. Conclusion: The weakness of the village community is related to two things, namely the behavior and knowledge of the community about the issues, so the implication is that there must be a strong effort from the central government to ensure that technology is more evenly distributed to all villagers.

• Journal of Korean Society on Water Environment
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• v.34 no.3
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• pp.251-269
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• 2018

In 1997, the environmental score (Q) corresponding the tolerance value of Korean benthic macroinvertebrate species and the related biotic score, the ecological score of benthic macroinvertebrates (ESB) were proposed; ESB was similar to Beck's biotic index or Chandler's biotic score. This study was carried out to revise the Q values of individual species and the assessment scheme of ESB based on the taxonomic performance and ecological information accumulated since then. The original ESB was renamed as TESB (total ESB), and AESB (average ESB) was newly proposed. AESB is calculated by dividing the TESB (for a given station) by the number of species present in the sample. In this study, TESB showed a positively skewed distribution, while AESB showed a negatively skewed distribution. The correlation between TESB and the concentration of $BOD_5$ was a little stronger than that of the original ESB. TESB showed a very strong correlation (correlation coefficient r = 0.98) with Margalef's species richness, of which correlation coefficient was higher than that of AESB (r = 0.85). AESB showed a strong correlation (r = -0.79) with the concentration of $BOD_5$, while TESB showed a weaker correlation (r = -0.67). Applying TESB and AESB together in an assessment of the environment may be comprehensive because the physical and chemical states of the environment can be evaluated together. AESB is less dependent on the sample size, while TESB tends to increase as the sample size increases. In the evaluation of the environment using TESB, it is necessary to standardize the methods on monitoring.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.3984-4005
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• 2017

Image recognition has become an increasingly important topic for its wide application. It is highly challenging when facing to large-scale database with large variance. The recognition systems rely on a key component, i.e. the low-level feature or the learned mid-level feature. The recognition performance can be potentially improved if the data distribution information is exploited using a more sophisticated way, which usually a function over hidden variable, model parameter and observed data. These methods are called generative score space. In this paper, we propose a discriminative extension for the existing generative score space methods, which exploits class label when deriving score functions for image recognition task. Specifically, we first extend the regular generative models to class conditional models over both observed variable and class label. Then, we derive the mid-level feature mapping from the extended models. At last, the derived feature mapping is embedded into a discriminative classifier for image recognition. The advantages of our proposed approach are two folds. First, the resulted methods take simple and intuitive forms which are weighted versions of existing methods, benefitting from the Bayesian inference of class label. Second, the probabilistic generative modeling allows us to exploit hidden information and is well adapt to data distribution. To validate the effectiveness of the proposed method, we cooperate our discriminative extension with three generative models for image recognition task. The experimental results validate the effectiveness of our proposed approach.

• Communications for Statistical Applications and Methods
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• v.20 no.5
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• pp.417-425
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• 2013

We consider an extended version of a logarithmic series distribution and discuss the estimation of its parameters by the method of moments and the method of maximum likelihood. Test procedures are suggested to test the significance of the additional parameter of this distribution and all procedures are illustrated with the help of real life data sets. In addition, a simulation study is conducted to assess the performance of the estimators.

• Communications for Statistical Applications and Methods
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• v.3 no.2
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• pp.197-204
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• 1996

We consider a two sample rank test for a bivariate mixture distribution based on Johnson's quantile score. The test statistic is simple to calculate and the exact distribution under the null hypothesis is obtained. A numerical example is given.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.179-185
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• 2021

The aim of this study is to examine the impact of board of directors' activity on the audit committee's effectiveness score among manufactured listed companies on Saudi Stock Exchange (Tadawul) for the period 2015-2017. The final sample of this study consists of 195 firm-year observations that represent manufactured companies listed on Saudi Stock Exchange (Tadawul) for the years 2015-2017. The data of this study in terms of board of directors' meetings, audit committee size and meetings, firm leverage, firm performance, and firm age were hand-collected from the annual reports of the considered companies. The Pooled OLS regression's result indicate that audit committee's effectiveness score is influenced by the board of directors' activity. This result gives support to the agency theory prediction. This result is also consistent with the complementary function of corporate governance mechanisms in which board of directors' activity complements the function of audit committee's effectiveness score. The result of this study should be useful for manufacturing companies, Saudi Stock Exchange, auditors, and regulators which relates to the association between board of directors' activity and audit committee's effectiveness score. This study provides a new empirical evidence on the impact of board activity on the audit committee's effectiveness score in an interesting context which is Saudi Arabia.

• The Korean Journal of Applied Statistics
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• v.22 no.1
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• pp.29-39
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• 2009

Among others, ROC and CAP curves are used to explore the discriminatory power between the defaults and non-defaults, based on the distribution of the probability of default in credit rating works. ROC and CAP curves are plotted in terms of various ratios of the probability of default. Each point on ROC and CAP curves is calculated according to cutting points (scores) for classifying between defaults and non-defaults. In this paper, adjusted ROC and CAP curves are proposed by using functions of ratios of the probability of default. It is possible to recognize the score corresponding to a point oil these adjusted curves, and we can identify the best score to show the optimal discriminatory power. Moreover, we discuss the relationships between the best score obtained from the adjusted ROC and CAP curves and the score corresponding to Kolmogorov - Smirnov statistic to test the homogeneous distribution functions of the defaults and non-defaults.

• Communications for Statistical Applications and Methods
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• v.18 no.2
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• pp.219-227
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• 2011

In this paper, we proposed a generalized bivariate negative binomial distribution allowing heterogeneous dispersions on two dependent variables based on a trivariate reduction technique. In this model, we propose the score and LR tests for testing the equality of dispersions and compare the efficiencies of the proposed tests using a Monte Carlo study. The Monte Carlo study shows that the proposed score and LR tests prove to be an efficient test for the equality of dispersions in the view of the significance level and power. However, the score test is easier to compute than the LR test and it shows a slightly better performance than the LR test from the Monte Carlo study, we suggest the use of score tests for testing the equality of dispersions on two dependent variables. In addition, an empirical example is provided to illustrate the results.