• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.627-641
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• 2016

In this paper, we consider a seemingly unrelated regression (SUR) model and propose a nonparametric Bayesian approach to SUR with a Dirichlet process mixture of normals for modeling an unknown error distribution. Posterior distributions are derived based on the proposed model, and the posterior inference is performed via Markov chain Monte Carlo methods based on the collapsed Gibbs sampler of a Dirichlet process mixture model. We present a simulation study to assess the performance of the model. We also apply the model to precipitation data over South Korea.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.275-287
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• 1998

The goal of this paper is to suggest the goodness-of-fit test statistic for the no effect model. The comparisons of powers on test statistics are conducted with three types alternative modles.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.769-777
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• 1998

In this study, various time series are analyzed to check nonlinearities of the data. The nonlinearity of a system can be investigated by testing the randomness of the time series data. To test the randomness, four nonparametric test statistics and a new test statistic, called the BDS statistic are used and the results and the results are compared. The Brock, Dechert, and Scheinkman (BDS) statistic is originated from the statistical properties of the correlation integral which is used for searching for chaos and has been shown very effective in distinguishing nonlinear structures in dynamic systems from random structures. As a result of application to linear and nonlinear models which are well known, the BDS statistic is found to be more effective than nonparametric test statistics in identifying nonlinear structure in the time series. Hydrologic time series data are fitted to ARMA type models and the statistics are applied to the residuals. The results show that the BDS statistic can distinguish chaotic nonlinearity from randomness and that the BDS statistic can also be used for verifying the validity of the fitted model.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.701-717
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• 2017

The interest of Korean society and government on future demographic structures is increasing due to rapid aging. Korea's mortality rate is decreasing, but the declined gap is variable. In this study, we compare the Lee-Carter, Lee-Miller, Booth-Maindonald-Smith model and functional data model (FDM) as well as Coherent FDM using non-parametric smoothing technique. We are then examine a reasonable model for projecting on mortality declined rate trend in terms of accuracy of mortality rate by ages and life expectancy. The possibility of using non-parametric techniques for the prediction of mortality in Korea was also examined. Based on the analysis results, FDM and Coherent FDM, which uses the non-parametric technique and reflects the trend of recent data, are excellent. As a result, FDM and Coherent FDM are good fit, and predictability is also excellent assuming no significant future changes.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.677-692
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• 2018

The total fertility rate of Korea was 1.05 in 2017, showing a return to the 1.08 level in the year 2005. 1.05 is a very low fertility level that is far from replacement level fertility or safety zone 1.5. The number may indicate a low fertility trap. It is therefore important to predict fertility than at any other time. In the meantime, we have predicted the age-specific fertility rate and total fertility rate by various statistical methods. When the data trend is disconnected or fluctuating, it applied a nonparametric method applying the smoothness and weight. In addition, the Bayesian method of using the pre-distribution of fertility rates in advanced countries with reference to the three-stage transition phenomenon have been applied. This paper examines which method is reasonable in terms of precision and feasibility by applying estimation, forecasting, and comparing the results of the recent variability of the Korean fertility rate with parametric, non-parametric and Bayesian methods. The results of the analysis showed that the total fertility rate was in the order of KOSTAT's total fertility rate, Bayesian, parametric and non-parametric method outcomes. Given the level of TFR 1.05 in 2017, the predicted total fertility rate derived from the parametric and nonparametric models is most reasonable. In addition, if a fertility rate data is highly complete and a quality is good, the parametric model approach is superior to other methods in terms of parameter estimation, calculation efficiency and goodness-of-fit.

• The Korean Journal of Applied Statistics
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• v.1 no.2
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• pp.66-81
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• 1987

A new nonparametric sequential testing procedure is proposed in the paper. Sequential observations are divided into equally sized groups and a nonparametric statistic, which is appropriate for testing the given hypotheses, is obtained from each group. Then Wald's sequential test is applied for the case where the log probability ratio statistic is replaced by the nonparametric statistic. The properties of such test are evaluated approximately by the Wiener process.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.4
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• pp.319-325
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• 1991

A nonparametric detection scheme which uses rank statistics for detection of known signals is considered in a special case of a generalized observation model. Specifically locally optimum rank detectors for detection of known deterministic singals in a singnal-dependent noise model are derived, and compared to those derived for the purely-additive noise model. Examples of the score functions are given, which constitutes the test statistics of the locally optimum rank detectors.

• The Korean Journal of Applied Statistics
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• v.3 no.1
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• pp.11-25
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• 1990

The objective of this paper is to propose a nonparametric distribution-free test for ordered alternatives in k crossed factor designs by using the concepts of combined factor and within-blocks ranks. We investigate the asymptotic normality of the proposed test statistic and the Pitman efficiencies. We also compared the small empirical powers of the tests considered in this paper by Monte Carlo study. Thus we can conclude that the proposed test is efficient and robust for the underlying distribution.

• Journal of the Korean Statistical Society
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• v.7 no.1
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• pp.17-26
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• 1978

For testing $\beta_i=\beta, i=1,...,k$, in the regression model $Y_{ij} = \alpha_i + \beta_ix_{ij} + e_{ij}, j=1,...,n_i$, a simple and robust test based on Kendall's tau is proposed. Its asymptotic distribution is proved to be chi-square under the null hypthesis and noncentral chi-square under an appropriate sequence of alternatives. For the optimal designs, the asymptotic relative efficiency of the proposed procedure with respect to the least squares procedure is the same as that of the Wilcoxon test with respect to the t-test.

• Proceedings of the Safety Management and Science Conference
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• 2012.04a
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• pp.573-577
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• 2012

Based on latest research, the parametric quality statistics cannot be used in non-normal process with demand pattern of many-variety and small-volume, since it involves extremely small sample size. The research proposes nonparametric quality statistics according to the number of lot or batch in the non-normal process. Additionally, the nonparametric Process Capability Index (PCI) is used with 14 identified non-normal distributions.