• 한국해양학회지
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• v.21 no.4
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• pp.193-202
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• 1986

Spatio-temporal variabilities of seawater temperature at 0 and 30m in the southeastern Hwanghae were studied by variance and empirical orthogonal function(EOF) analysis of long records of temperature between 1967 and 1982. The spatial distribution of monthly mean sea surface temperature has a pattern similar to the long-term annual mean which decreases from south to north. On the contrary, the total variance computed from the annual mean of sea surface temperature(SST) increases from south to north. The variance of SST is found to be two times greater than that at 30m in the study area except coastal area south of Kyunggi Bay. The important variance of temperature seem s to be closely associated with the seasonal change of temperature because the first and second modes of EOF having a seasonal cycle explain 97.6% and 85.2% of variances at 0 and 30m, respectively. There is a large difference in temperature between the northern and southern parts of the study area during winter, while the difference becomes very small during summer. This might reflect that in summer the heat gain of sea surface from the incoming radiation is much more important than the heat loss or the oceanic heat advection. In summer coastal waters south of the Kyunggi Bay and around Mokpo are observed to be colder than offshore waters due to tidal mixing.

• Journal of Korea Water Resources Association
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• v.34 no.4
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• pp.357-364
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• 2001

Sometimes the observed data is too small to discriminate it from noise of the instrument. Say, the data can be recorded as below DL(Detection Level) value. Even though the data below Detection Level(BDL) is small vague, it can be resulted in wrong estimates for mean and variance. However, in practice, the BDL data is generally eliminated as N.D. (Not Detected) and do not record it in Korea. This study investigates the distributions according to the data values of ammonia concentration (NH$_3$-N) in Puyeo intake. Also we try to find out DL value and an appropriate method for the estimations of mean and variance of BDL values that can be discriminate the distributions. The DL is estimated by trial and error method. The appropriate method for the estimations of mean and variance of above the detection level(ADL)and BDL dada sets is selected, and the mean and variance are estimated. As a result, it is found that the Bias Corrected Maximum Likelihood Estimator is the most accurate method for NH$_3$-N in Puyeo intake.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.411-425
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• 2021

Accelerated failure time (AFT) model represents a linear relationship between the log-survival time and covariates. We are interested in the inference of covariate's effect affecting the variation of survival times in the AFT model. Thus, we need to model the variance as well as the mean of survival times. We call the resulting model mean and variance AFT (MV-AFT) model. In this paper, we propose a variable selection procedure of regression parameters of mean and variance in MV-AFT model using penalized likelihood function. For the variable selection, we study four penalty functions, i.e. least absolute shrinkage and selection operator (LASSO), adaptive lasso (ALASSO), smoothly clipped absolute deviation (SCAD) and hierarchical likelihood (HL). With this procedure we can select important covariates and estimate the regression parameters at the same time. The performance of the proposed method is evaluated using simulation studies. The proposed method is illustrated with a clinical example dataset.

• East Asian Economic Review
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• v.20 no.2
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• pp.169-190
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• 2016

This paper tests the weak-form efficient market hypothesis for Korean industry-sorted portfolios. Based on a panel variance ratio approach, we find significant mean reversion of stock returns over long horizons in the pre Asian currency crisis period but little evidence in the post-crisis period. Our empirical findings are consistent with the fact that Korea accelerated its integration with international financial market by implementing extensive capital liberalization since the crisis.

• Journal of applied mathematics & informatics
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• v.23 no.1_2
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• pp.479-488
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• 2007

A sequential procedure is proposed in order to construct one-sided confidence intervals for a normal mean with guaranteed coverage probability and ${\beta}-protection$ when the normal mean and variance are identical. First-order asymptotic properties on the sequential sample size are found. The derived results hold with uniformity in the total parameter space or its subsets.

• Journal of Korean Society for Quality Management
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• v.22 no.2
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• pp.41-50
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• 1994

Consider a canning process where cans are filled with an expensive ingredient. Cans weighting above the specified limit are sold in a regular market for a fixed price, and underfilled cans are emptied and refilled at the expense of a reprocessing cost. In this paper, the effect of measurement error on the determination of the optimal process mean for a canning process is examined. It is assumed that the quantity X of ingredient in a can is normally distributed with unknown mean and known variance, and the observed value Y of X is also normally distributed with known mean and variance. A profit model is constructed which involves selling price. cost of ingredients, reprocessing cost. and cost from an accepted nonconforming can, and methods of finding the optimal process mean and the cutoff value on Y are presented. It is shown that the optimal process mean increases. and the expected profit decreases when the measurement error is relatively large in comparison to the process variance.

• The Journal of the Acoustical Society of Korea
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• v.34 no.4
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• pp.316-320
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• 2015

In this paper, the pole filtering concept is applied to the Mel-frequency cepstral coefficient (MFCC) feature vectors in the conventional cepstral mean normalization (CMN) and cepstral mean and variance normalization (CMVN) frameworks. Additionally, performance of the cepstral mean and scale normalization (CMSN), which uses scale normalization instead of variance normalization, is evaluated in speech recognition experiments in noisy environments. Because CMN and CMVN are usually performed on a per-utterance basis, in case of short utterance, they have a problem that reliable estimation of the mean and variance is not guaranteed. However, by applying the pole filtering and scale normalization techniques to the feature normalization process, this problem can be relieved. Experimental results using Aurora 2 database (DB) show that feature normalization method combining the pole-filtering and scale normalization yields the best improvements.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.131-142
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• 1999

Estimators for domains and approximate estimators of their variance are derived using post-stratified complex sample. Furthermore we propose an adjusted variance estimator of a domain mean in case of considering the post-stratified complex sample as simple random sample. A simulation study based on the data of Farm Household Economy Survey is presented to compare variance estimators numerically. From the study we showed that our adjusted variance estimator compensate for the under-estimation problem considerably.

• Journal of the Korea Safety Management & Science
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• v.3 no.3
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• pp.175-190
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• 2001

We propose, a new process capability index $C_{psk}$(WV) applying the weighted variance control charting method for non-normally distributed. The main idea of the weighted variance method(WVM) is to divide a skewed or asymmetric distribution into two normal distributions from its mean to create two new distributions which have the same mean but different standard deviations. In this paper we propose an example, a distributions generated from the Johnson family of distributions, to demonstrate how the weighted variance-based process capability indices perform in comparison with another two non-normal methods, namely the Clements and the Wright methods. This example shows that the weighted valiance-based indices are more consistent than the other two methods in terms of sensitivity to departure to the process mean/median from the target value for non-normal processes. Second method show using the percentage nonconforming by the Pearson, Johnson and Burr systems. This example shows a little difference between the Pearson system and Burr system, but Johnson system underestimated than the two systems for process capability.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.153-156
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• 1999

The technique is reported of identifying parameters in off-line process. The technique demands that closed-loop system consists of a reference and two-degree-of-freedom controllers (TDFC) in real process. A model process is the same as the real process except their parameters. Deviations are differences between the reference and the output of the plant or the model. The technique is based on minimizing identification error between the two deviations. The parameter differences between the plant and the model are characterized of mean value and of variance which are derived from the identification error. Consequently, the algorithm which identifies the unknown plant parameters is shown by minimizing the mean value and the variance, respectively, within double convergence loops. The technique is applied to course change of a ship. The plant deviation at the first trial is shown to occur in replacing the nominal parameters by the default parameters. The plant deviation at the second trial is shown to not occur in replacing the nominal parameters by the identified parameters. Hence, the identification technique is confirmed to be feasible in the real field.