• Title/Summary/Keyword: Variance estimation

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Slope Rotatability of Second Order Response Surface Regression Models with Correlated Errors

  • Jung, Hyang-Sook;Park, Sung-Hyun
    • Proceedings of the Korean Statistical Society Conference
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    • 2005.05a
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    • pp.95-100
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    • 2005
  • In this paper a class of multifactor designs for estimating the slope of second order response surface regression models with correlated errors is considered. General conditions for second order slope rotatability over all directions and also with respect to the maximum directional variance in case of k=2 have been derived assuming errors have a general correlated error structure. And we consider the measures for evaluating slope rotatability with correlated errors similar to in case of uncorrelated error structures.

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Monitoring with VSR Charts and Change Point Estimation

  • Lee, Jae-Heon;Park, Chang-Soon
    • Proceedings of the Korean Statistical Society Conference
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    • 2005.05a
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    • pp.191-196
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    • 2005
  • Knowing the time of the process change could lead to quicker identification of the responsible special cause and less process down time, and it could help to reduce the probability of incorrectly identifying the special cause. In this paper, we propose a MLE of the process change point when control charts with the fixed sampling rate (FSR) scheme or the variable sampling rate (VSR) scheme monitor a process to detect changes in the process mean and/or variance of a normal quality variable.

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GEOMETRICAL PROPERTIES OF t-DISTRIBUTION

  • CHO, BONG SIK;BAEK, HOH YOO
    • Honam Mathematical Journal
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    • v.28 no.3
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    • pp.433-438
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    • 2006
  • The Fisher information matrix plays a significant role in statistical inference in connection with estimation and properties of variance of estimators. In this paper, the parameter space of the t-distribution using its Fisher's matrix is defined. The Riemannian and scalar curvatures to parameter space are calculated.

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A Weibull Model Building Technique for Reliability Assessment with Limited failure Data (신뢰도 평가에서 제한된 데이터를 이용한 와이블분포 모형화 기법)

  • Kim, Gwang-Won
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.55 no.3
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    • pp.109-115
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    • 2006
  • The Weibull distribution is a good candidate for accurate probabilistic model with its rich shape-forming ability and relatively simple CDF(cumulative distribution function). If there are sufficient information to get convincible mean and variance for a probabilistic event, reliable parameters of the Weibull distribution can be determined uniquely. However, sufficient information is not given as usual. There needs more deliberate model building method for that case. This Paper presents an effective parameter estimation technique for Weibull distribution with limited failure data.

A Study of Parameter Estimation with the Prior-Information by Using the Multiple Stratification (사전정보가 있는 경우 다중층화를 이용한 모수추정연구)

  • 이해용
    • Journal of Applied Reliability
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    • v.3 no.2
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    • pp.117-125
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    • 2003
  • In sampling survey, prior-information about population has been generally ignored to estimate parameters. But if there is some believable prior-information about population, it is very useful to get more efficiency estimators by using the prior-information. This paper shows how to estimate the parameter, to evaluate the variance of the estimator, and to un-biasness of the estimator by using multiple stratification with prior-information about survey population. The proposed method is illustrated with a set of hypothetical data. The results show that the proposed estimator is very efficiency and strongly recommendable.

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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
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    • v.6 no.4
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    • pp.251-255
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    • 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.

A Genome-wide Association Study of Preferred Primal Cuts of Hanwoo Cattle Using Single-step GBLUP (한우 부분육 선호부위에 대한 ssGBLUP을 활용한 GWAS 분석)

  • Lee, Jae Gu;Park, Byoungho;Park, Mi Na;Alam, M.;Kim, Sidong;Do, Changhee;Choi, Tae Jeong
    • Journal of agriculture & life science
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    • v.50 no.3
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    • pp.99-117
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    • 2016
  • Data on primal cuts were collected from 1,829 steers of Hanwoo progeny testing programs, between 2010 and 2015 for the ssGWAS. SNP data were analyzed by using Illumina Bovine 50K Beadchip. The SNP data that matches with phenotype data was 674 animals. As a first step, the genomic estimated breeding value(GEBV) of the loin and rib cuts were estimated, which was used in the estimation of SNP marker effects and their variances related to the traits. Then, the estimated variance explained by each marker was expressed as a proportion to the total genetic variance. Finally, the SNP loci and their significance to any possible QTL were examined. Among the 20 best SNP loci explaining a larger proportion of SNP variance to the total genetic variance for tender loin yield, the region between 12,812,193 ~ 12,922,313bp on BTA 10 harbored a cluster of SNPs that explained about 7.32 to 7.34% of the total genetic variance. For strip loin yield, a peak for higher effects for multiple SNPs was found in BTA24, between 38,158,543 and 38,347,278bp distances, which explained about 8.36 to 8.56% of the observed variance for this trait. For loin yield had relatively smaller effects in terms of the total genetic variance. Therefore, loin yield might be affected by a few loci with moderate effects and many other loci with smaller effects across the genome.

A Fast Motion Estimation Algorithm using Adaptive Search According to Importance of Search Ranges (탐색영역의 중요도에 따라 적응적인 탐색을 이용한 고속 움직임 예측 알고리즘)

  • Kim, Tae Hwan;Kim, Jong Nam;Jeong, Shin Il
    • Journal of Korea Multimedia Society
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    • v.18 no.4
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    • pp.437-442
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    • 2015
  • Voice activity detection is very important process that voice activity separated form noisy speech signal for speech enhance. Over the past few years, many studies have been made on voice activity detection, but it has poor performance in low signal to noise ratio environment or fickle noise such as car noise. In this paper, it proposed new voice activity detection algorithm using ensemble variance based on wavelet band entropy and soft thresholding method. We conduct a survey in a lot of signal to noise ratio environment of car noise to evaluate performance of the proposed algorithm and confirmed performance of the proposed algorithm.

Design of suboptimal robust kalman filter using LMI approach (LMI기법을 이용한 준최적 강인 칼만 필터의 설계)

  • 진승희;윤태성;박진배
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.1477-1480
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    • 1997
  • This paper is concerned with the design of a suboptimal robust Kalman filter using LMI approach for system models in the state space, which are subjected to parameter uncertainties in both the state and measurement atrices. Under the assumption that augmented system composed of the uncertain system and the state estimation error dynamics should be stable, a Lyapunov inequality is obtained. And from this inequaltiy, the filter design problem can be transformed to the gneric LMI problems i.e., linear objective minimization problem and generalized eigenvalue minimization problem. When applied to uncertain linear system modles, the proposed filter can provide the minimum upper bound of the estimation error variance for all admissible parameter uncertainties.

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An estimation procedure with updated sample (패널조사에서 표본 변경을 고려한 추정)

  • 박진우
    • The Korean Journal of Applied Statistics
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    • v.10 no.2
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    • pp.367-374
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    • 1997
  • In panel surveys it is necessary to manage both sampling frame and sample units across time. When sample is updated according to the change of its frame, it should be incorporated in the estimation procedure. This paper derives the bias of the conventional estimator caused by neglecting the change of sample, and provides a bias-adjusted estimator with its variance.

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