• 제목/요약/키워드: Variance Values

검색결과 1,030건 처리시간 0.027초

국부 분산을 이용한 장면 전환 적응 비트율 제어 (Scence Change Adaptive Bit Rate Control Using Local Variance)

  • 이호영;김기석;박영식;송근원;남재열;하영호
    • 한국통신학회논문지
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    • 제22권4호
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    • pp.675-684
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    • 1997
  • The bit rate control algorithm which is capable of handing scene change is proposed. In MPEG-2 TM5, block variance is used to measure block activity. But block variance is not consistent with human visual system and does not differenciate the distribution of pixel values within the block. In target bit allocation process of TM5, global complexity, obtained by results of previous coded pictures, is used. Since I pictures are spaced relatively far apart, their complexity estimate is not very accurate. In the proposed algorithm local variance is used to measure block activity and detect scene change. Local variance, using deviation from the mean of neighboring pixels, well represents the distribution of pixel values within the block. If scene change is detected, the local variance information is used for target bit allocation process. Allocating target bits for I picture, the average local variance difference between previous and current I picture is considered. The experimental results show that the proposed algorithm can detect scene change very precisely and gives better picture quality and higher PSNR values than MPEG-2 TM5.

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Critical Multiple Correlation Coefficient for Improving Mean and Variance in Augmenting Hydrologic Samples

  • Heo, Jun-Haeng
    • Korean Journal of Hydrosciences
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    • 제6권
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    • pp.13-22
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    • 1995
  • The augmenting hydrologic data using a correlation procedure has been used to improve the estimates of the mean and variance at the site of interest with short record when one or more near by sites with longer records are available. The variance of the unbiased maximum likelihood estimator of $ derived by Moran based on the multivariate normal distribytion is modified into the form of Matalas and Jacobs for the biveriate normal distribution to get the critical minimum values of the multiple correlation coefficient which give the improvement for estimating the variance at the site of interest. Those values are tabulated for various lengths of short records and the number of sites.

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시험조건 변화에 따른 연기밀도 특성 조사 (Smoke Density Values to the variance of test conditions)

  • 이덕희;이철규;정우성;김선옥
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2004년도 춘계학술대회 논문집
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    • pp.339-345
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    • 2004
  • In this study we reported the Smoke Density values of interior materials of railroad passenger car and investigated the specific smoke density(Ds) by NBS smoke chamber to the variance of some test conditions. First we compared the result of Ds from ISO 5659-2 with that from ASTM E 662 for same material. Secondary studied the Ds value to the variance of specimen shape and thickness and to the variance of other conditions.

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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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    • 제28권2호
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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.

Variance Estimation for Imputed Survey Data using Balanced Repeated Replication Method

  • Lee, Jun-Suk;Hong, Tae-Kyong;Namkung, Pyong
    • Communications for Statistical Applications and Methods
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    • 제12권2호
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    • pp.365-379
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    • 2005
  • Balanced Repeated Replication(BRR) is widely used to estimate the variance of linear or nonlinear estimators from complex sampling surveys. Most of survey data sets include imputed missing values and treat the imputed values as observed data. But applying the standard BRR variance estimation formula for imputed data does not produce valid variance estimators. Shao, Chen and Chen(1998) proposed an adjusted BRR method by adjusting the imputed data to produce more accurate variance estimators. In this paper, another adjusted BRR method is proposed with examples of real data.

상수각 형질의 유전력 (Heritabilities of Some Characters of Mulberry Trees)

  • 장권열;한경수;민병렬
    • 한국잠사곤충학회지
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    • 제10권
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    • pp.41-43
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    • 1969
  • 상수각형질의 유전력을 알고자 우리나라 상수주요품종인 개량서반, 일지뢰, 노상, 수원상호의 4개품종을 재료로 유전력을 추정한 바 그 결과를 요약하면 다음과 같다. 1. 상수형질중 절간수의 유전력은 96.95로 제일 높고 주당지수의 유전력은 49.48로서 제일 낮았다. 2. 지조장, 지조직경, 지총중, 고지조중, 신소엽중, 그리고 정엽중의 유전력은 66-69의 값으로 절간수와 주당지수의 값의 중간치를 보였다. 이상의 결과로 상수의 형질중 절간수는 환경에 의한 변동이 적고 주당지수는 변동이 심하며 기타형질은 이들의 중간정도임을 알 수 있었다.

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수문자료 확충을 위한 다중상관계수의 한계최소치 유도 (Derivation of the Critical Minimum Values of the Multiple Correlation Coefficient for Augmenting Hydrologic Samples)

  • 허준행
    • 물과 미래
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    • 제27권1호
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    • pp.133-140
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    • 1994
  • 주변 관측지점의 자료가 유용한 경우 관측자료가 짧은 지점의 평균과 분산 추정치를 개선하기 위하여 상관계수를 이용한 수문자료 확충을 이용하여왔다. 본 연구에서는 관측지점의 분산 추정치를 개선하기 위한 다중 상관계수의 한계최소치를 얻기 위하여, 다변량 정규분포에 근거하여 Moran이 유도한 확충자료 분산( ${{\sigma}_v}^2$ )의 불편 최우도추정량의 분산식을 Matalas와 Jacobs가 2변량 정규분포에 근거하여 유도한 식의 형태로 변형하였으며, 다양한 자료수와 지점수에 따라 다중상관계수의 한계최소치를 도표화했다.

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Nonnegative estimates of variance components in a two-way random model

  • Choi, Jaesung
    • Communications for Statistical Applications and Methods
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    • 제26권4호
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    • pp.337-346
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    • 2019
  • This paper discusses a method for obtaining nonnegative estimates for variance components in a random effects model. A variance component should be positive by definition. Nevertheless, estimates of variance components are sometimes given as negative values, which is not desirable. The proposed method is based on two basic ideas. One is the identification of the orthogonal vector subspaces according to factors and the other is to ascertain the projection in each orthogonal vector subspace. Hence, an observation vector can be denoted by the sum of projections. The method suggested here always produces nonnegative estimates using projections. Hartley's synthesis is used for the calculation of expected values of quadratic forms. It also discusses how to set up a residual model for each projection.

Jackknife Variance Estimation under Imputation for Nonrandom Nonresponse with Follow-ups

  • Park, Jinwoo
    • Journal of the Korean Statistical Society
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    • 제29권4호
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    • pp.385-394
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    • 2000
  • Jackknife variance estimation based on adjusted imputed values when nonresponse is nonrandom and follow-up data are available for a subsample of nonrespondents is provided. Both hot-deck and ratio imputation method are considered as imputation method. The performance of the proposed variance estimator under nonrandom response mechanism is investigated through numerical simulation.

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Why do we get Negative Variance Components in ANOVA

  • Lee, Jang-Taek
    • Communications for Statistical Applications and Methods
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    • 제8권3호
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    • pp.667-675
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    • 2001
  • The usefulness of analysis of variance(ANOVA) estimates of variance components is impaired by the frequent occurrence of negative values. The probability of such an occurrence is therefore of interest. In this paper, we investigate a variety of reasons for negative estimates under one way random effects model. It can be shown, through simulation, that this probability increases when the number of treatments is too small for fixed total observations, unbalancedness of data is severe, ratio of variance components is too small, and data may contain many outliers.

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