• Title/Summary/Keyword: mean-variance

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Detection of the Normal Population with the Largest Absolute Value of Mean

  • Kim, Woo-Chul;Jeong, Gyu-Jin
    • Journal of the Korean Statistical Society
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    • v.22 no.1
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    • pp.71-81
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    • 1993
  • Among k independent normal populations with unknown means and a common unknown variance, the problem of detecting the population with the largest absolute value of mean is considered. This problem is formulated in a manner close to the framework of testing hypotheses, and the maximum error probability and the minimum power are considered. The power charts necessary to determine the sample size are provided. The problem of detecting the population with the smallest absolute value of mean is also considered.

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Lindley Type Estimators When the Norm is Restricted to an Interval

  • Baek, Hoh-Yoo;Lee, Jeong-Mi
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.4
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    • pp.1027-1039
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    • 2005
  • Consider the problem of estimating a $p{\times}1$ mean vector $\theta(p\geq4)$ under the quadratic loss, based on a sample $X_1$, $X_2$, $\cdots$, $X_n$. We find a Lindley type decision rule which shrinks the usual one toward the mean of observations when the underlying distribution is that of a variance mixture of normals and when the norm $\parallel\;{\theta}-\bar{{\theta}}1\;{\parallel}$ is restricted to a known interval, where $bar{{\theta}}=\frac{1}{p}\;\sum\limits_{i=1}^{p}{\theta}_i$ and 1 is the column vector of ones. In this case, we characterize a minimal complete class within the class of Lindley type decision rules. We also characterize the subclass of Lindley type decision rules that dominate the sample mean.

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Saddlepoint Approximation to the Distribution of General Statistic (일반적 통계량의 분포함수에 대한 안부점 근사)

  • 나종화
    • The Korean Journal of Applied Statistics
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    • v.11 no.2
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    • pp.287-302
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    • 1998
  • Saddlepoint approximation to the distribution function of sample mean(Daniels, 1987) is extended to the case of general statistic in this paper. The suggested approximation methods are applied to derive the approximations to the distributions of some statistics, including sample valiance and studentized mean. Some comparisons with other methods show that the suggested approximations are very accurate for moderate or small sample sizes. Even in extreme tail the accuracies are also maintained.

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Accuracy Measures of Empirical Bayes Estimator for Mean Rates

  • Jeong, Kwang-Mo
    • Communications for Statistical Applications and Methods
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    • v.17 no.6
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    • pp.845-852
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    • 2010
  • The outcomes of counts commonly occur in the area of disease mapping for mortality rates or disease rates. A Poisson distribution is usually assumed as a model of disease rates in conjunction with a gamma prior. The small area typically refers to a small geographical area or demographic group for which very little information is available from the sample surveys. Under this situation the model-based estimation is very popular, in which the auxiliary variables from various administrative sources are used. The empirical Bayes estimator under Poissongamma model has been considered with its accuracy measures. An accuracy measure using a bootstrap samples adjust the underestimation incurred by the posterior variance as an estimator of true mean squared error. We explain the suggested method through a practical dataset of hitters in baseball games. We also perform a Monte Carlo study to compare the accuracy measures of mean squared error.

Performance of a Bayesian Design Compared to Some Optimal Designs for Linear Calibration (선형 캘리브레이션에서 베이지안 실험계획과 기존의 최적실험계획과의 효과비교)

  • 김성철
    • The Korean Journal of Applied Statistics
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    • v.10 no.1
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    • pp.69-84
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    • 1997
  • We consider a linear calibration problem, $y_i = $$\alpha + \beta (x_i - x_0) + \epsilon_i$, $i=1, 2, {\cdot}{\cdot},n$ $y_f = \alpha + \beta (x_f - x_0) + \epsilon, $ where we observe $(x_i, y_i)$'s for the controlled calibration experiments and later we make inference about $x_f$ from a new observation $y_f$. The objective of the calibration design problem is to find the optimal design $x = (x_i, \cdots, x_n$ that gives the best estimates for $x_f$. We compare Kim(1989)'s Bayesian design which minimizes the expected value of the posterior variance of $x_f$ and some optimal designs from literature. Kim suggested the Bayesian optimal design based on the analysis of the characteristics of the expected loss function and numerical must be equal to the prior mean and that the sum of squares be as large as possible. The designs to be compared are (1) Buonaccorsi(1986)'s AV optimal design that minimizes the average asymptotic variance of the classical estimators, (2) D-optimal and A-optimal design for the linear regression model that optimize some functions of $M(x) = \sum x_i x_i'$, and (3) Hunter & Lamboy (1981)'s reference design from their paper. In order to compare the designs which are optimal in some sense, we consider two criteria. First, we compare them by the expected posterior variance criterion and secondly, we perform the Monte Carlo simulation to obtain the HPD intervals and compare the lengths of them. If the prior mean of $x_f$ is at the center of the finite design interval, then the Bayesian, AV optimal, D-optimal and A-optimal designs are indentical and they are equally weighted end-point design. However if the prior mean is not at the center, then they are not expected to be identical.In this case, we demonstrate that the almost Bayesian-optimal design was slightly better than the approximate AV optimal design. We also investigate the effects of the prior variance of the parameters and solution for the case when the number of experiments is odd.

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Estimation of Systolic Blood Pressure using PTTL (PTTL을 이용한 수축기 혈압추정)

  • Kil, Se-Kee;Kwan, Jang-Woo;Yoon, Kwang-Sub;Lee, Sang-Min
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.6
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    • pp.1095-1101
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    • 2008
  • The desirable method to diagnose abnormal blood pressure is to measure and manage blood pressure continuously and regularly. However, the sphygmomanometers that are based on a cuff have faults in that they can not measure the blood pressure continuously and they cause an unpleasant feeling. Therefore, it is essential to develop a new measuring method that causes no pain and that can obtain blood pressure continuously without any unpleasant feeling. Thus, we propose here a regression method to estimate the systolic blood pressure by using the PTTL(pulse transit time on leg) with some body parameters which are chosen from the relational analysis with systolic blood pressure. The data we use to make the regression model were obtained in triplicate from each of 50 males who were from 18 to 35 years. And we made estimation experiments of blood pressure on 10 males who did not take part in the making the regression model. According to the results, the proposed method showed a mean error of 4.00 mmHg and the standard variance was 2.45 mmHg. When we comparing the results of the proposed method with the rule of American National Standards Institute of the Association of the Advancement of Medical Instruments(ANSI/AAMI), the results satisfied the rule of a mean error less than 5 mmHg and a standard variance less than 8 mmHg. Therefore we were able to validate the usefulness of the proposed method.

Robust Newsvendor Model With Random Yield and Customer Balking (불확실한 수율과 고객이탈행위를 고려한 강건한 뉴스벤더 모델)

  • Jung, Uk;Lee, Se Won
    • Journal of Korean Society for Quality Management
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    • v.40 no.4
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    • pp.441-452
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    • 2012
  • Purpose: In this paper, we have considered a problem of newsvendor model in an environment of random yields in quality and customer balking behavior, in which only the mean and the variance of the demand are known. In practice, the distributional information of the demand is very limited and only the mean and variance are guessed by experience. In addition, due to the customers balking behavior occurring when the available inventory level decreases, the product's demand becomes a function of inventory level so that the classical newsvendor's optimal order quantity is no longer optimal. Methods: We have developed an optimal order quantity model that enables us to incorporate the random yield of a product and the customer balking information such as a threshold inventory level of balking and the corresponding probability of a sale during the balking. Results: We illustrated the concepts developed here through simple numerical examples and showed the robustness of our model in a various setting of parameters. Conclusion: This paper provides a useful analysis showing that our distribution-specific and distribution-free approach to the optimal order quantity in the newsboy model can act as an effective tools to match supply with demand for these product lines.

Role of linking parameters in Pulse-Coupled Neural Network for face detection

  • Lim, Young-Wan;Na, Jin-Hee;Choi, Jin-Young
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1048-1052
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    • 2004
  • In this work, we have investigated a role of linking parameter in Pulse-Coupled Neural Network(PCNN) which is suggested to explain the synchronous activities among neurons in the cat cortex. Then we have found a method to determine the linking parameter for a satisfactory face detection performance in a given color image. Face detection algorithm which uses the color information is independent on pose, size and obstruction of a face. But the use of color information encounters some problems arising from skin-tone color in the background, intensity variation within faces, and presence of random noise and so on. Depending on these conditions, PCNN's linking parameters should be selected an appropriate values. First we obtained the mean and variance of the skin-tone colors by experiments. Then, we introduced a preprocess that the pixel with a mean value of skin-tone colors has the highest level value (255) and the other pixels have values between 0 and 255 according to normal distribution with a variance. This preprocessing leads to an easy decision of the linking parameter of the Pulse-Coupled Neural Network. Through experiments, it is verified that the proposed method can improve the face detection performance compared to the existing methods.

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A study on the determinants of job stress responses of the staff nurses (일반 간호사의 직무 스트레스 반응에 대한 결정 요인)

  • Kim, Jeong-Hee;Park, Sung-Ae
    • Journal of Korean Academy of Nursing Administration
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    • v.9 no.2
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    • pp.217-232
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    • 2003
  • Purpose : This paper was attempted to identify the job stress related factors among the staff nurses and to provide the basic data concerning development of stress management program focused on hospitals. Method : The subjects were 309 staff nurses at two general hospitals in Seoul. Data were collected with self-reported questionnaires and analyzed by SPSS-PC+10.0 for descriptive analysis, ANOVA, stepwise multiple regression, factor analysis. Results : The subjects exhibit significantly highest level of 'the participation in decision making factor'. The mean score of 'control coping strategies' was higher than 'avoid coping strategies'. The mean scores of social support and stress responses were high. The main factor that affected the stress responses was 'the job characteristic factor' and it was explained 23.0% out of the total variance of the stress responses. Also, it would be explained 42.6% out of the total variance of the stress responses with 'the control coping strategies, work overload factors, social support, and participation in decision making factors'. Conclusion: For developing the hospital- focused stress management program for staff nurses, 'the participation in decision making factors' and 'the job characteristics' should be considered. Also, the organizational efforts and supports should be required to support and use of 'control coping strategies' of nurses

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Analysis of Modified Digital Costas Loop Part II : Performance in the Presence of Noise (변형된 디지탈 Costas loop에 관한 연구 (II) 잡음이 있을 경우의 성능 해석)

  • 정해창;은종관
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.19 no.3
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    • pp.37-45
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    • 1982
  • This paper is a sequel of the Part I paper[1] on the modified digital Costas loop. In this Part II we analyze the performance of the system in the presence of noise. It is shown that, when the input signal is corrupted by additive white Gaussian noise, the noise process in the loop becomes Rician as a result of the tan-1 (.) function of the phase error detector. Steady state probability density functions of phase errors of the first-and second-order loops have been obtained by solving the Chapman-Kolmogorov equation numerically. Also, the mean and variance of phase error in the steady state have been obtained analytically, and are compared with the results obtained by computer simulation.

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