• Title/Summary/Keyword: Variance Value

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

  • Lee Duck-Hee;Lee Cheul Kyu;Jung Woo-Sung;Kim Sun-ok
    • Proceedings of the KSR Conference
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    • 2004.06a
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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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Smoke Density Characteristics of the FRP to the variance of test method, resin type and specimen shape (FRP 복합재의 시험조건 변화에 따른 연기 위해성 평가)

  • 이덕희;정우성;김용기;김선옥
    • Proceedings of the KSR Conference
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    • 2002.05a
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    • pp.567-571
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    • 2002
  • In this study we reported the Smoke Density test method of interior panel 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 E662 for same phenol FRP Secondary studied the Ds value to the variance of resin type and to the variance of specimen shape.

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Does the Variance of Customer Satisfaction Matter for Firm Performance?

  • Lee, Eun Young;Yoo, Shijin;Lee, Dong Wook
    • Asia Marketing Journal
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    • v.18 no.4
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    • pp.51-76
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    • 2017
  • Although much attention has been paid to customer satisfaction (CS) as a leading indicator of firm performance, few studies have investigated the role of CS distribution across individual customers. With 10 years of National Customer Satisfaction Index (NCSI) data in Korea, we examine the relationship between the variance of CS and key corporate performance measures such as revenue, profit, Tobin's q, and stock return. There are three main findings. First, we confirm the findings of previous studies that the average CS for a firm is related to the firm's economic performance. Second, we find a moderating effect of CS variance such that the relationship between the level of CS and firm performance is attenuated by the variance of CS. Finally, the variance of CS is found to directly affect firm performance over and above the CS level effect. More specifically, the variance decreases sales and stock return.

An Investigation on the Effect of Utility Variance on Choice Probability without Assumptions on the Specific Forms of Probability Distributions (특정한 확률분포를 가정하지 않는 경우에 효용의 분산이 제품선택확률에 미치는 영향에 대한 연구)

  • Won, Jee-Sung
    • Korean Management Science Review
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    • v.28 no.1
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    • pp.159-167
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    • 2011
  • The theory of random utility maximization (RUM) defines the probability of an alternative being chosen as the probability of its utility being perceived as higher than those of all the other competing alternatives in the choice set (Marschak 1960). According to this theory, consumers perceive the utility of an alternative not as a constant but as a probability distribution. Over the last two decades, there have been an increasing number of studies on the effect of utility variance on choice probability. The common result of the previous studies is that as the utility variance increases, the effect of the mean value of the utility (the deterministic component of the utility) on choice probability is reduced. This study provides a theoretical investigation on the effect of utility variance on choice probability without any assumptions on the specific forms of probability distributions. This study suggests that without assumptions of the probability distribution functions, firms cannot apply the marketing strategy of maximizing choice probability (or market share), but can only adopt the strategy of maximizing the minimum or maximum value of the expected choice probability. This study applies the Chebyshef inequality and shows how the changes in utility variances affect the maximum of minimum of choice probabilities and provides managerial implications.

GARCH-X(1, 1) model allowing a non-linear function of the variance to follow an AR(1) process

  • Didit B Nugroho;Bernadus AA Wicaksono;Lennox Larwuy
    • Communications for Statistical Applications and Methods
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    • v.30 no.2
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    • pp.163-178
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    • 2023
  • GARCH-X(1, 1) model specifies that conditional variance follows an AR(1) process and includes a past exogenous variable. This study proposes a new class from that model by allowing a more general (non-linear) variance function to follow an AR(1) process. The functions applied to the variance equation include exponential, Tukey's ladder, and Yeo-Johnson transformations. In the framework of normal and student-t distributions for return errors, the empirical analysis focuses on two stock indices data in developed countries (FTSE100 and SP500) over the daily period from January 2000 to December 2020. This study uses 10-minute realized volatility as the exogenous component. The parameters of considered models are estimated using the adaptive random walk metropolis method in the Monte Carlo Markov chain algorithm and implemented in the Matlab program. The 95% highest posterior density intervals show that the three transformations are significant for the GARCHX(1, 1) model. In general, based on the Akaike information criterion, the GARCH-X(1, 1) model that has return errors with student-t distribution and variance transformed by Tukey's ladder function provides the best data fit. In forecasting value-at-risk with the 95% confidence level, the Christoffersen's independence test suggest that non-linear models is the most suitable for modeling return data, especially model with the Tukey's ladder transformation.

An Efficient Iterative Decoding Stop Criterion using the Variance Value of LLR (LLR의 분산값을 이용한 효율적인 반복중단 알고리즘)

  • 심병섭;정대호;정성태;정경택;김환용
    • Proceedings of the IEEK Conference
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    • 2003.07a
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    • pp.178-181
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    • 2003
  • In this paper, it proposes the efficient iterative decoding stop criterion using the variance value of LLR. It is verifying that the proposal iterative decoding stop criterion can be reduced the average iterative decoding number compared to conventional schemes with a negligible degradation of the error performance.

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Influence of Inbreeding Depression on Genetic (Co)Variance and Sire-by-Year Interaction Variance Estimates for Weaning Weight Direct-Maternal Genetic Evaluation

  • Lee, C.;Pollak, E.J.
    • Asian-Australasian Journal of Animal Sciences
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    • v.10 no.5
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    • pp.510-513
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    • 1997
  • This study examined the effects of ignoring inbreeding depression on (co)variance components for weaning weight through the use of Monte Carlo simulation. Weaning weight is of particular interest as a trait for which additive direct and maternal genetic components exist and there then is the potential for a direct-maternal genetic covariance. Ignoring inbreeding depression in the analytical model (.8 kg reduction of phenotypic value per 1% inbreeding) led to biased estimates of all genetic (co) variance components, all estimates being larger than the true values of the parameters. In particular, a negative bias in the direct-maternal genetic covariance was observed in analyses that ignored inbreeding depression. A small spurious sire-by-year interaction variance was also observed.

Volatility of Export Volume and Export Value of Gwangyang Port (광양항의 수출물동량과 수출액의 변동성)

  • Mo, Soo-Won;Lee, Kwang-Bae
    • Journal of Korea Port Economic Association
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    • v.31 no.1
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    • pp.1-14
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    • 2015
  • The standard GARCH model imposing symmetry on the conditional variance, tends to fail in capturing some important features of the data. This paper, hence, introduces the models capturing asymmetric effect. They are the EGARCH model and the GJR model. We provide the systematic comparison of volatility models focusing on the asymmetric effect of news on volatility. Specifically, three diagnostic tests are provided: the sign bias test, the negative size bias test, and the positive size bias test. This paper shows that there is significant evidence of GARCH-type process in the data, as shown by the test for the Ljung-Box Q statistic on the squared residual data. The estimated unconditional density function for squared residual is clearly skewed to the left and markedly leptokurtic when compared with the standard normal distribution. The observation of volatility clustering is also clearly reinforced by the plot of the squared value of residuals of export volume and values. The unconditional variance of both export volumes and export value indicates that large shocks of either sign tend to be followed by large shocks, and small shocks of either sign tend to follow small shocks. The estimated export volume news impact curve for the GARCH also suggests that $h_t$ is overestimated for large negative and positive shocks. The conditional variance equation of the GARCH model for export volumes contains two parameters ${\alpha}$ and ${\beta}$ that are insignificant, indicating that the GARCH model is a poor characterization of the conditional variance of export volumes. The conditional variance equation of the EGARCH model for export value, however, shows a positive sign of parameter ${\delta}$, which is contrary to our expectation, while the GJR model exhibits that parameters ${\alpha}$ and ${\beta}$ are insignificant, and ${\delta}$ is marginally significant. That indicates that the asymmetric volatility models are poor characterization of the conditional variance of export value. It is concluded that the asymmetric EGARCH and GJR model are appropriate in explaining the volatility of export volume, while the symmetric standard GARCH model is good for capturing the volatility.

Development of a Simplified Statistical Methodology for Nuclear Fuel Rod Internal Pressure Calculation

  • Kim, Kyu-Tae;Kim, Oh-Hwan
    • Nuclear Engineering and Technology
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    • v.31 no.3
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    • pp.257-266
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    • 1999
  • A simplified statistical methodology is developed in order to both reduce over-conservatism of deterministic methodologies employed for PWR fuel rod internal pressure (RIP) calculation and simplify the complicated calculation procedure of the widely used statistical methodology which employs the response surface method and Monte Carlo simulation. The simplified statistical methodology employs the system moment method with a deterministic approach in determining the maximum variance of RIP The maximum RIP variance is determined with the square sum of each maximum value of a mean RIP value times a RIP sensitivity factor for all input variables considered. This approach makes this simplified statistical methodology much more efficient in the routine reload core design analysis since it eliminates the numerous calculations required for the power history-dependent RIP variance determination. This simplified statistical methodology is shown to be more conservative in generating RIP distribution than the widely used statistical methodology. Comparison of the significances of each input variable to RIP indicates that fission gas release model is the most significant input variable.

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A Study on the Image Restoration with Wavelet Packet and Noise Variance (웨이블릿 패킷과 노이즈 분산에 의한 영상의 복원에 관한 연구)

  • 박윤옥;이승용;류광렬
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.05a
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    • pp.733-736
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    • 2003
  • The denoising for image restoration with wavelet packet and noise variance is presented. The image denoising has the threshold value used absolute average value of noise variance and the translated wavelet packet. The results on the experiment improved over 10% and 5% than the denoising based on wavelet transform and wavelet packet respectively.

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