• Communications for Statistical Applications and Methods
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• v.24 no.3
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• pp.211-226
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• 2017

The chain-ladder method, for which run-off data is employed is popularly used in the rate-adjustment and loss-reserving practices of non-life-insurance and health-insurance companies. The method is applicable when the underlying assumption of a consistent development pattern is in regards to a cumulative loss payment after the occurrence of an insurance event. In this study, a modified chain-ladder algorithm is proposed for when the assumption is considered to be only partially appropriate for the given run-off data. The concept of a structural-change point in the run-off data and its reflection in the estimation of unpaid loss amounts are discussed with numerical illustrations. Experience data from private health insurance coverage in Korea were analyzed based on the suggested method. The performance in estimation of loss reserve was also compared with traditional approaches. We present evidence in this paper that shows that a reflection of a structural-change point in the chain-ladder method can improve the risk management of the relevant insurance products. The suggested method is expected to be utilized easily in actuarial practice as the algorithm is straightforward.

• Journal of The Korean Society of Grassland and Forage Science
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• v.11 no.3
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• pp.169-174
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• 1991

For simple estimation of pasture production and nutritive value in relation to height of orchardgrass (Ductylis glomumtu L.), the experiment was carried out in a pasture mixture dominated by orchardgrass. The samples of grasses were harvested at the heights of about 30, 40, 50, 70 and 90 cm at the first harvest under different percentage of 100 (grass coverage): 0 (bareland), 80 : 20, 60 : 40, 40 : 60 and 20 : 80, respectively. As the height of orchardgrass was increased, fresh and dry matter (DM) yield were significantly increased. The regression equation between DM yield (Y) and height (X) was Y=ll. 5390 X- 146.60 (r=O. 9414 * * ). Also the higher bareland, the lower pasture production was observed. As the plant height at the first harvest was increased, the contents of crude (C) protein, C. fat, C. ash and relative feed value were markedly decreased. On the other hand, the contents of C. fiber, NFE, NDF. ADF, cellulose and lignin were significantly increased, respectively. The higher height, the lower DM digestibility was found. The equation between digestibility (Y) and height (X) was Y=- 0.2193 X+ 80.99 (r = - 0.9862**). Considering DM yield, digestibility and crude protein, the optimum height of orchardgrass at the first harvest was 59 to 67crn for better pasture production and nutritive value.

• The Korean Journal of Applied Statistics
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• v.18 no.3
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• pp.607-615
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• 2005

Recently the interval estimation of a binomial proportion is revisited in various literatures. This is mainly due to the erratic behavior of the coverage probability of the will-known Wald confidence interval. Various alternatives have been proposed. Among them, Agresti-Coull confidence interval has been recommended by Brown et al. (2001) with other confidence intervals for large sample, say n $\ge$ 40. On the other hand, a noninformative Bayesian approach called Polya posterior often produces statistics with good frequentist's properties. In this note, an interval estimator is developed using weighted Polya posterior. The resulting interval estimator is essentially the Agresti-Coull confidence interval with some improved features. It is shown that the weighted Polys posterior produce an effective interval estimator for small sample size and a severely skewed binomial distribution.

• Communications for Statistical Applications and Methods
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• v.22 no.5
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• pp.435-443
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• 2015

Two phase sampling design is useful to increase estimation efficiency using deep stratification, improved non-response adjustment and reduced coverage bias. The same sampling units are commonly used for the first and the second phases in complex two-phase sampling design. In this paper we consider a sampling scheme where the first phase sampling units are clusters and the second phase sampling units are list samples. Using selected clusters in first phase requires that we list up elements in the selected clusters from the first phase and then use the list as a secondary sampling frame for the second phase sampling design. Then we select second phase samples from the listed sampling frame. We suggest an estimator based on the complex two-phase sampling design with different sampling units of each phase. Also the estimated variances of the estimator obtained by using classic and replication variance methods are considered and compared using simulation studies. For real data analysis, 2010 Korea Farm Household Economy Survey (KFHES) and 2011 Korea Agriculture Survey (KAS) are used.

• The Journal of the Korean life insurance medical association
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• v.30 no.2
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• pp.8-11
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• 2011

Insurance medicine has been known to medical risk selection. The role of insurance medicine is sound maintenance of insurance system. So it's function is medical underwriting of life risks. However, emerging market has insufficient medical epidemiological research that is necessary for estimation of extra-risk and such market is usually lack of full understanding of life insurance among insurance customers. This problem makes difficult of performing the medical underwriting, as an original insurance medicine. Medical contributions at the stage of claims adjudication comparing the coverage provided in the product, with the information provided in the claims, based on medical records and the agreement between them. This is called medical verification. The insurance doctors can also use their medical knowledge to help the claims staff with informing claimants about the medical basis of claims decisions.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.14-14
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• 2003

Given a sequence ｛ $X_{n}$｝ of independent and identically distributed random variables with F, a sequential procedure for the p-th quantile ξ$_{P}$= $F^{-1}$ (P), 0$\beta$-protection. Some asymptotic properties for the proposed procedure and of an involved stopping time are proved: asymptotic consistency, asymptotic efficiency and asymptotic normality. From one of the results an effect of smoothing based on kernel functions is discussed. The results are also extended to the contaminated case.e.e.

• The Korean Journal of Applied Statistics
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• v.11 no.1
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• pp.151-161
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• 1998

We study the bootstrap interval estimation for survival function in the Koziol-Green model. We construct the approximate bootstrap confidence intervals for survival function and prove the strong consistency for the bootstrap estimator of survival function. Finally we show that the approximate bootstrap confidence intervals are better in terms of coverage probability than confidence intervals based on asymptotic normal distribution and transformations of survival function via Monte Carlo simulation study.

• IE interfaces
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• v.25 no.4
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• pp.422-430
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• 2012

In this article, we introduced the estimation method by 'Safety Integrity Level'(SIL) for the criterion of safety assurance and performed a case study on a flame scanner. SIL requires probabilistic evaluation of each set of equipment used to reduce risk in a safety related system. FMEDA(Failure Modes, Effects and Diagnostic Analysis) method is widely used to evaluate the safety levels and provides information on the failure rates and failure mode distributions necessary to calculate a diagnostic coverage factor for a part or a component. Basically, two parameters resulting from FMEDA are used for SIL classification of the device : SFF(Safe Failure Fraction) and PFD(Probability of Failure on Demand). In this case study, it is concluded that the flame scanner is designed to fulfill the condition of SIL 3 in the aspect of SFF and PFD.

• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.501-509
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• 2009

Recently the interval estimation of binomial proportions is revisited in various literatures. This is mainly due to the erratic behavior of the coverage probability of the well-known Wald confidence interval. Various alternatives have been proposed. Among them, the Agresti-Coull confidence interval, the Wilson confidence interval and the Bayes confidence interval resulting from the noninformative Jefferys prior were recommended by Brown et al. (2001). However, unlike the binomial distribution case, little is known about the properties of the confidence intervals in finite population sampling. In this note, the property of confidence intervals is investigated in anile population sampling.

• Journal of Communications and Networks
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• v.10 no.2
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• pp.127-136
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• 2008

For mobile wireless systems with full frequency reuse, co-channel interference near the cell coverage boundaries has a significant impact on the signal reception performance. This paper addresses an approach to efficiently mitigate the effect of downlink co-channel interference when multi-antenna terminals are used in cellular environments, by proposing a signal detection strategy combined with a system-level coordination for dynamic frequency reuse. We demonstrate the utilization of multi-antennas to perform spatial demultiplexing of both the desired signal and interfering signals from adjacent cells results in significant improvement of spectral efficiency compared to the maximal ratio combining (MRC) performance, especially when an appropriate frequency reuse based on the traffic loading condition is coordinated among cells. Both analytic expressions for the capacity and experimental results using the adaptive modulation and coding (AMC) are used to confirm the performance gain. The robustness of the proposed scheme against varying operational conditions such as the channel estimation error and shadowing effects are also verified by simulation results.