• Communications for Statistical Applications and Methods
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• v.16 no.6
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• pp.1055-1066
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• 2009

Many articles have considered a hybrid censoring scheme, which is a mixture of Type-I and Type-II censoring schemes. We introduce a double hybrid censoring scheme and derive some approximate maximum likelihood estimators(AMLEs) of the scale parameter for the half logistic distribution under the proposed double hybrid censored samples. The scale parameter is estimated by approximate maximum likelihood estimation method using two different Taylor series expansion types. We also obtain the maximum likelihood estimator(MLE) and the least square estimator(LSE) of the scale parameter under the proposed double hybrid censored samples. We compare the proposed estimators in the sense of the mean squared error. The simulation procedure is repeated 10,000 times for the sample size n = 20(10)40 and various censored samples. The performances of the AMLEs and MLE are very similar in all aspects but the MLE and LSE have not a closed-form expression, some numerical method must be employed.

• Journal of the Korean Data and Information Science Society
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• v.11 no.1
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• pp.37-45
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• 2000

Consider the problem of estimating a $p{\times}1$ mean vector ${\underline{\theta}}(p{\geq}4)$ under the quadratic loss, based on a sample ${\underline{x}_{1}},\;{\cdots}{\underline{x}_{n}}$. We find an optimal decision rule within the class of Lindley type decision rules which shrink the usual one toward the mean of observations when the underlying distribution is that of a variance mixture of normals and when the norm ${\parallel}\;{\underline{\theta}}\;-\;{\bar{\theta}}{\underline{1}}\;{\parallel}$ is known, where ${\bar{\theta}}=(1/p){\sum_{i=1}^p}{\theta}_i$ and $\underline{1}$ is the column vector of ones.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.641-648
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• 2007

We propose the new sampling method, called modified ranked ordering set sampling (MROSS). Kim and Kim (2003) suggested the sign test using the ranked ordering set sampling (ROSS), and showed that the asymptotic relative efficiency (ARE) of ROSS against RSS for sign test increases as sample size does. We propose the estimator for the population mean using MROSS. The relative precision (RP) of estimator of the population mean using MROSS method with respect to the usual estimator using modified RSS is higher, and when the underlying distribution is skewed, the bias of the proposed estimator is smaller than that of several ranked set sampling estimators.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.201-213
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• 1998

We address the problem of choosing the most economic mean value for an automatic filling operation on a production line through the sampling inspection. If quality characteristic of a unit is less than inspection specification then the goods is not accepted. Otherwise, it is accepted. The lots that the numbers of non-conforming units in a sample are larger than the allowable number of non-conforming units are rejected. The non-conforming units in the rejected lots are separated by the screening inspection. The non-conforming units separated are sold in discount price. We assume that quality characteristic is larger-the-better characteristic, the distribution of quality characteristic is normal distribution, and the standard deviation of the distribution is known. This paper presents total expected profit function model considering sales revenue, inspection costs, and material costs. The manufacturing process mean value maximizing total expected profit is determined, and the results of the process target value and total expected profit is analyzed as coefficients change.

• 한국데이터정보과학회:학술대회논문집
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• 2005.10a
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• pp.13-26
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• 2005

In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and location parameter of the exponential distribution based on multiply Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error for various censored samples. We also obtain the approximate maximum likelihood estimator (AMLE) of the reliability function by using the proposed estimators. And then we compare the proposed estimators in the sense of the mean squared error.

• Journal of the Korean Statistical Society
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• v.3 no.1
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• pp.3-12
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• 1974

The two-stage sequential test, suggested by Baker [2] for testing hypotheses $H_0:\mu=\mu_0$ and $H_1:\mu=\mu_1$ of $N(\mu,\sigma^2)$ with the unknown $\sigma^2$ would not be amenable for applications unles some cluses on the choice of the first-stage sample size are available. The study in this paper is intended to shed some light on the size of the first-stage sample. An approximate method is used to estimate an optimal initial sample size that minimizes the average sample number. In brief, the optimal size is a strictly monotone decreasing function of the quantity $(\mu_1-\mu_0)/\sigma$. Empirical and simulation results are used to ascertain the negligible effect of possible errors due to approximations and assumptions used.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3076-3092
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• 2020

An IKPCA-ELM-based intrusion detection method is developed to address the problem of the low accuracy and slow speed of intrusion detection caused by redundancies and high dimensions of data in the network. First, in order to reduce the effects of uneven sample distribution and sample attribute differences on the extraction of KPCA features, the sample attribute mean and mean square error are introduced into the Gaussian radial basis function and polynomial kernel function respectively, and the two improved kernel functions are combined to construct a hybrid kernel function. Second, an improved particle swarm optimization (IPSO) algorithm is proposed to determine the optimal hybrid kernel function for improved kernel principal component analysis (IKPCA). Finally, IKPCA is conducted to complete feature extraction, and an extreme learning machine (ELM) is applied to classify common attack type detection. The experimental results demonstrate the effectiveness of the constructed hybrid kernel function. Compared with other intrusion detection methods, IKPCA-ELM not only ensures high accuracy rates, but also reduces the detection time and false alarm rate, especially reducing the false alarm rate of small sample attacks.

• Journal of the Korean Statistical Society
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• v.7 no.2
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• pp.95-98
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• 1978

This note deals with the estimations of the variance of a normal distribution $N(\theta,c\theta^2)$ where c, the square of coefficient of variation is assumed to be known. This amounts to the estimation of $\theta^2$. The minimum variance estimator among all unbiased estimators linear in $\bar{x}^2$ and $s^2$ where $\bar{x}$ and $s^2$ are the sample mean and variance, respectively, and the minimum risk estimator in the class of all estimators linear in $\bar{x}^2$ and $s^2$ are obtained. It is shown that the suggested estimators are BAN.

• Journal of the Korean Data and Information Science Society
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• v.19 no.3
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• pp.959-965
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• 2008

We shall propose several estimators for the scale parameter in a uniform distribution with the presence of a half-triangle outlier, and obtain mean squared errors(MSE's) for their proposed estimators. And we shall compare numerically efficiencies for proposed several estimators of the scale parameter in a uniform distribution with the presence of a half-triangle outlier in the small sample sizes.

• Communications for Statistical Applications and Methods
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• v.5 no.1
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• pp.225-230
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• 1998

By assuming a singly right cenosred sample, we propose the approximate maximum likelihood estimator (AMLE) of the scale parameter of the p-dimensional Rayleigh distribution. We compare the proposed estimator in ·terms of the mean squared error through Monte Carlo methods.