• Title/Summary/Keyword: variance to mean ratio

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Variance estimation for distribution rate in stratified cluster sampling with missing values

  • Heo, Sunyeong
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.2
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    • pp.443-449
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    • 2017
  • Estimation of population proportion like the distribution rate of LED TV and the prevalence of a disease are often estimated based on survey sample data. Population proportion is generally considered as a special form of population mean. In complex sampling like stratified multistage sampling with unequal probability sampling, the denominator of mean may be random variable and it is estimated like ratio estimator. In this research, we examined the estimation of distribution rate based on stratified multistage sampling, and determined some numerical outcomes using stratified random sample data with about 25% of missing observations. In the data used for this research, the survey weight was determined by deterministic way. So, the weights are not random variable, and the population distribution rate and its variance estimator can be estimated like population mean estimation. When the weights are not random variable, if one estimates the variance of proportion estimator using ratio method, then the variances may be inflated. Therefore, in estimating variance for population proportion, we need to examine the structure of data and survey design before making any decision for estimation methods.

Impact of target spectra variance of selected ground motions on seismic response of structures

  • Xu, Liuyun;Zhou, Zhiguang
    • Earthquakes and Structures
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    • v.23 no.2
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    • pp.115-128
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    • 2022
  • One common method to select input ground motions to predict dynamic behavior of structures subjected to seismic excitation requires spectral acceleration (Sa) match target mean response spectrum. However, dispersion of ground motions, which explicitly affects the structural response, is rarely discussed in this method. Generally, selecting ground motions matching target mean and variance has been utilized as an appropriate method to predict reliable seismic response. The goal of this paper is to investigate the impact of target spectra variance of ground motions on structural seismic response. Two sets of ground motions with different target variances (zero variance and minimum variance larger than inherent variance of the target spectrum) are selected as input to two different structures. Structural responses at different heights are compared, in terms of peak, mean and dispersion. Results show that increase of target spectra variance tends to increase peak floor acceleration, peak deformation and dispersions of response of interest remarkably. To short-period structures, dispersion increase ratios of seismic response are close to that of Sa of input ground motions at the first period. To long-period structures, dispersions of floor acceleration and floor response spectra increase more significantly at the bottom, while dispersion increase ratios of IDR and deformation are close to that of Sa of input ground motions at the first period. This study could further provide useful information on selecting appropriate ground motion to predict seismic behavior of different types of structures.

Mean Estimation in Two-phase Sampling (이중추출에서 모평균 추정)

  • 김규성;김진석;이선순
    • The Korean Journal of Applied Statistics
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    • v.14 no.1
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    • pp.13-24
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    • 2001
  • In this paper, we investigated mean estimation methods in two-phase sampling. Under the fixed expected cost we reviewed the optimal sample sizes, minimum variances and approximate unbiased variance estimators for usual ratio estimator, stratified sample mean with proportional allocation and Rao's allocation of the second phase sample. Also we proposed combined ratio estimator, which uses both ratio estimation and stratification and derived optimal sample size, minimum variance and unbiased variance estimator. Through a limited simulation study, we compared estimators by design effects and came to know that ratio estimator is more efficient than stratified sample mean in some cases and inefficient in the other cases, but combined ratio estimator is more efficient than others in most cases.

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Selection of Signal-to-Noise Ratios through Simple Data Analysis (망목특성에서의 자료분석을 통한 SN비의 선택)

  • Lim, Yong Bin
    • Journal of Korean Society for Quality Management
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    • v.22 no.4
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    • pp.1-12
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    • 1994
  • For quality improvement, Taguchi emphasizes the reduction of variation of the quality characteristic. Taguchi has used the signal to noise ratios for achieving minimum dispersion of the quality characteristic with its location adjusted to some desired target value. At each setting of design factors, the variance of the quality characteristic could be affected by the mean. In most cases, as the mean get larger, the variance tends to increase, The Taguchi's SN ratio corresponds to the case that the variance is proportional to the square of the mean. But the variance can increase faster or slower than the square of the mean. We propose to infer a linking relationship of the variance and mean through simple data analysis technique, and then use a reasonable SN ratio.

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Development and Application of Process Incapability Index including Capability Analysis of Inspection or Gage System (검사/계측시스템의 능력분석을 포함한 비공정능력지수의 개발과 적용)

  • 민성진;김계완;류정현;윤덕균
    • Journal of Korean Society for Quality Management
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    • v.30 no.1
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    • pp.118-132
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    • 2002
  • This paper presents a process incapability index to provide manager with various information of process and to reduce cost. The introduced process incapability indices indicate information about mean and variance of manufacturing process and variance of inspection process to evaluate process capability using ratio of variance and difference between target and mean to specification. This model can be used by the scale of six sigma management.

Monitoring System for Abnormal Cutting States in the Drilling Operation using Motor Current (모터전류를 이용한 드릴가공에서의 절삭이상상태 감시 시스템)

  • Kim, H.Y.;Ahn, J.H.
    • Journal of the Korean Society for Precision Engineering
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    • v.12 no.5
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    • pp.98-107
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    • 1995
  • The in-process detection of drill wear and breakage is one of the most importnat technical problems in unmaned machining system. In this paper, the monitoring system is developed to monitor abnormal drilling states such as drill breakage, drill wear and unstable cutting using motor current. Drill breakage is detected by level monitoring. Tool wear is classified by fuzzy pattern recognition. The key feature for classification of tool wear is the estimated flank wear which is calculated by the proposed flank wear model. The characteristic of the model is not sensitive to the variation of cutting conditions but is sensitive to drill wear state. Unstable cutting states due to the unsmooth chip disposal and the overload are monitored by the variance/mean ratio of spindle motor current. Variance/mean ratio also includes the information about the prediction of drill wear and drill breakage. The evaluation experiments have shown that the developed system works very well.

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Nonlinear Goal Programming Approach for Robust Parameter Experiments (로버스트 변수모형의 비선형 목표계획법 접근방법)

  • Lee, Sang-Heon
    • Journal of the military operations research society of Korea
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    • v.28 no.1
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    • pp.47-66
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    • 2002
  • Instead of using signal-to-noise ratio, we attempt to optimize both the mean and variance responses using dual response optimization technique. The alternative experimental strategy analyzes a robust parameter design problem to obtain the best settings that give a target condition on the mean while minimizing its variance. The mean and variance are treated as the two responses of interest to be optimized. Unlike to the crossed array and combined array approaches, our experimental setup requires replicated runs for each control factor's treatment under noise sampling. When the postulated response models are true, they enable the coefficients to be estimated and the desired performance measure to be analyzed more efficiently. The procedure and illustrative example are given for the dual response optimization techniques of nonlinear goal programming.

Biased SNR Estimation using Pilot and Data Symbols in BPSK and QPSK Systems

  • Park, Chee-Hyun;Hong, Kwang-Seok;Nam, Sang-Won;Chang, Joon-Hyuk
    • Journal of Communications and Networks
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    • v.16 no.6
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    • pp.583-591
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    • 2014
  • In wireless communications, knowledge of the signal-to-noise ratio is required in diverse communication applications. In this paper, we derive the variance of the maximum likelihood estimator in the data-aided and non-data-aided schemes for determining the optimal shrinkage factor. The shrinkage factor is usually the constant that is multiplied by the unbiased estimate and it increases the bias slightly while considerably decreasing the variance so that the overall mean squared error decreases. The closed-form biased estimators for binary-phase-shift-keying and quadrature phase-shift-keying systems are then obtained. Simulation results show that the mean squared error of the proposed method is lower than that of the maximum likelihood method for low and moderate signal-to-noise ratio conditions.

Multi-Characteristic Robust Design Methodology Based on Designer's Preference (설계자 선호도를 고려한 다특성 강건설계법)

  • 김경모
    • Journal of Korean Society for Quality Management
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    • v.29 no.1
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    • pp.47-61
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    • 2001
  • The ever increasing demands for enhanced competitiveness of engineered products require a "designing-in-quality" strategy that can effectively and efficiently incorporate multiple design objectives into design. Robust design can be viewed as a multi-characteristic design problem requiring tradeoffs between mean and variance characteristics. Firstly this paper analyzes the intrinsic preference of the traditional SN ratio on mean and variance, and secondly presents a new design metric for a robust design using concepts from utility theory to accurately capture designer′s intent and preference on mean and variance. The steps to apply the proposed design metric as the robust design criterion in an orthogonal array based engineering experimentation is presented with the aid of a demonstrative case study. The performance of the proposed design metric is tested, and the results are discussed.

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An estimator of the mean of the squared functions for a nonparametric regression

  • Park, Chun-Gun
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.3
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    • pp.577-585
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    • 2009
  • So far in a nonparametric regression model one of the interesting problems is estimating the error variance. In this paper we propose an estimator of the mean of the squared functions which is the numerator of SNR (Signal to Noise Ratio). To estimate SNR, the mean of the squared function should be firstly estimated. Our focus is on estimating the amplitude, that is the mean of the squared functions, in a nonparametric regression using a simple linear regression model with the quadratic form of observations as the dependent variable and the function of a lag as the regressor. Our method can be extended to nonparametric regression models with multivariate functions on unequally spaced design points or clustered designed points.

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