• Title/Summary/Keyword: mean-variance

Search Result 2,052, Processing Time 0.027 seconds

Efficiency of Estimation for Parameters by Use of Variance Reduction Techniques (분산감소기법을 이용한 파라미터 추정의 효율성)

  • Kwon Chi-myung
    • Journal of the Korea Society for Simulation
    • /
    • v.14 no.3
    • /
    • pp.129-136
    • /
    • 2005
  • We develop a variance reduction technique applicable in one simulation experiment whose purpose is to estimate the parameters of a first order linear model. This method utilizes the control variates obtained during the course of simulation run under Schruben and Margolin's method (S-M method). The performance of this method is shown to be similar in estimating the main effects, and to be superior to S-M method in estimating the overall mean response in a given model. We consider that a proposed method may yield a better result than S-M method if selected control variates are highly correlated with the response at each design point.

  • PDF

Optimal Transmission Expansion Planning Considering the Uncertainties of Power Market (전력시장 불확실성을 고려한 최적 송전시스템 확장계획)

  • Son, Min-Kyun;Kim, Jin-O
    • The Transactions of The Korean Institute of Electrical Engineers
    • /
    • v.57 no.4
    • /
    • pp.560-566
    • /
    • 2008
  • Today, as the power trades between generation companies and power customer are liberalized, the uncertainty level of operated power system is rapidly increased. Therefore, transmission operators as decision makers for transmission expansion are required to establish a deliberate investment plan for effective operations of transmission facilities considering forecasted conditions of power system. This paper proposes the methodology for the optimal solution of transmission expansion in deregulated power system. The paper obtains the expected value of transmission congestion cost for various scenarios by using occurrence probability. In addition, the paper assumes that increasing rates of loads are the probability distribution and indicates the location of expanded transmission line, the time for transmission expansion with the minimum cost for the future by performing the Montecarlo simulation. To minimize the investment risk as the variance of the congestion cost, Mean-Variance Markowitz portfolio theory is applied to the optimization model by the penalty factor of the variance. By the case study, the optimal solution for transmission expansion plan considering the feature of market participants is obtained.

ESTIMATING VARIOUS MEASURES IN NORMAL POPULATION THROUGH A SINGLE CLASS OF ESTIMATORS

  • Sharad Saxena;Housila P. Singh
    • Journal of the Korean Statistical Society
    • /
    • v.33 no.3
    • /
    • pp.323-337
    • /
    • 2004
  • This article coined a general class of estimators for various measures in normal population when some' a priori' or guessed value of standard deviation a is available in addition to sample information. The class of estimators is primarily defined for a function of standard deviation. An unbiased estimator and the minimum mean squared error estimator are worked out and the suggested class of estimators is compared with these classical estimators. Numerical computations in terms of percent relative efficiency and absolute relative bias established the merits of the proposed class of estimators especially for small samples. Simulation study confirms the excellence of the proposed class of estimators. The beauty of this article lies in estimation of various measures like standard deviation, variance, Fisher information, precision of sample mean, process capability index $C_{p}$, fourth moment about mean, mean deviation about mean etc. as particular cases of the proposed class of estimators.

Pattern Analysis of Sea Surface Temperature Distribution in the Southeast Sea of Korea Using a Weighted Mean Center (가중공간중심을 활용한 한국 남동해역의 표층수온 분포 패턴 분석)

  • KIM, Bum-Kyu;YOON, Hong-Joo;KIM, Tae-Hoon;CHOI, Hyun-Woo
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.23 no.3
    • /
    • pp.263-274
    • /
    • 2020
  • In the Southeast Sea of Korea, a cold water mass is formed intensively in summer every year, causing frequent abnormal sea conditions. In order to analyze the spatial changes of sea surface temperature distribution in this area, ocean fields buoy data observed at Gori and Jeongja and reanalyzed sea surface temperature(SST) data from GHRSST Level 4 were used from June to September 2018. The buoy data were used to analyze the time-series water temperature changes at two stations, and the GHRSST data were used to calculate the daily SST variance and weighted mean center(WMC) across the study area. When the buoy's water temperature was lowered, the variance of SST in the study area trend to increase, but it did not appear consistently for the entire period. This is because GHRSST is a reanalysis data that does not reflect sensitive changes in water temperature along the coast. As such, there is a limit to grasping the local small-scale water temperature change in the coast or detecting the location and extent of the cold water zone only by the statistical variance representing the SST change in the entire sea area. Therefore, as a result of using WMC to quantitatively determine the spatial location of the cold water mass, when the cold water zone occurred, WMC was located in the northwest sea area from the mean center(MC) of the study area. This means that it is possible to quantitatively identify where and to what extent the distribution of cold surface water temperature appears through SST's WMC location information, and we could see the possibility of WMC's use in detecting the scale of cold water zones and the extent of regional spread in the future.

Histogram Equalization Using Centroids of Fuzzy C-Means of Background Speakers' Utterances for Majority Voting Based Speaker Identification (다수 투표 기반의 화자 식별을 위한 배경 화자 데이터의 퍼지 C-Means 중심을 이용한 히스토그램 등화기법)

  • Kim, Myung-Jae;Yang, Il-Ho;Yu, Ha-Jin
    • The Journal of the Acoustical Society of Korea
    • /
    • v.33 no.1
    • /
    • pp.68-74
    • /
    • 2014
  • In a previous work, we proposed a novel approach of histogram equalization using a supplement set which is composed of centroids of Fuzzy C-Means of the background utterances. The performance of the proposed method is affected by the size of the supplement set, but it is difficult to find the best size at the point of recognition. In this paper, we propose a histogram equalization using a supplement set for majority voting based speaker identification. The proposed method identifies test utterances using a majority voting on the histogram equalization methods with various sizes of supplement sets. The proposed method is compared with the conventional feature normalization methods such as CMN(Cepstral Mean Normalization), MVN(Mean and Variance Normalization), and HEQ(Histogram Equalization) and the histogram equalization method using a supplement set.

On Bounds for Moments of Unimodal Distributions

  • Sharma, R.;Bhandaria, R.
    • Communications for Statistical Applications and Methods
    • /
    • v.21 no.3
    • /
    • pp.201-212
    • /
    • 2014
  • We provide a simple basic method to find bounds for higher order moments of unimodal distributions in terms of lower order moments when the random variable takes value in a given finite real interval. The bounds for moments in terms of the geometric mean of the distribution are also derived. Both continuous and discrete cases are considered. The bounds for the ratio and difference of moments are obtained. The special cases provide refinements of several well-known inequalities, such as Kantorovich inequality and Krasnosel'skii and Krein inequality.

Estimation of the Lorenz Curve of the Pareto Distribution

  • Kang, Suk-Bok;Cho, Young-Suk
    • Communications for Statistical Applications and Methods
    • /
    • v.6 no.1
    • /
    • pp.285-292
    • /
    • 1999
  • In this paper we propose the several estimators of the Lorenz curve in the Pareto distribution and obtain the bias and the mean squared error for each estimator. We compare the proposed estimators with the uniformly minimum variance unbiased estimator (UMVUE) and the maximum likelihood estimator (MLE) in terms of the mean squared error (MSE) through Monte Carlo methods and discuss the results.

  • PDF

Admissible Hierarchical Bayes Estimators of a Multivariate Normal Mean Shrinking towards a Regression Surface

  • Cho, Byung-Yup;Choi, Kuey-Chung;Chang, In-Hong
    • Communications for Statistical Applications and Methods
    • /
    • v.3 no.2
    • /
    • pp.205-216
    • /
    • 1996
  • Consider the problem of estimating a multivariate normal mean with an unknown covarience matrix under a weighted sum of squared error losses. We first provide hierarchical Bayes estimators which shrink the usual (maximum liklihood, uniformly minimum variance unbiased) estimator towards a regression surface and then prove the admissibility of these estimators using Blyth's (1951) method.

  • PDF

Improvement of the Modified James-Stein Estimator with Shrinkage Point and Constraints on the Norm

  • Kim, Jae Hyun;Baek, Hoh Yoo
    • Journal of Integrative Natural Science
    • /
    • v.6 no.4
    • /
    • pp.251-255
    • /
    • 2013
  • For the mean vector of a p-variate normal distribution ($p{\geq}4$), the optimal estimation within the class of modified James-Stein type decision rules under the quadratic loss is given when the underlying distribution is that of a variance mixture of normals and when the norm ${\parallel}{\theta}-\bar{\theta}1{\parallel}$ it known.