• Journal of the Korean Data and Information Science Society
• /
• v.15 no.4
• /
• pp.899-910
• /
• 2004

In this paper we have proposed a new loss function, namely, non-linear exponential(NLINEX) loss function, which is quite asymmetric in nature. We obtained the Bayes estimator under exponential(LINEX) and squared error(SE) loss functions. Moreover, a numerical comparison among the Bayes estimators of power function distribution under SE, LINEX, and NLINEX loss function have been made.

• Journal of Korean Society for Quality Management
• /
• v.30 no.3
• /
• pp.66-78
• /
• 2002

Process capability indices are being used as indicators for measurements of process capability for SPC of quality assurance system in industries. In view of the enhancement of customer satisfaction, process capability indices in which loss functions are used to deal with the economic loss In the processes deviated from the target, are in an adequate representation of the customer's perception of quality In this connection, the loss function has become increasingly important in quality assurance. Taguchi uses a modified form of the quadratic loss function to demonstrate the need to consider the proximity to the target while assessing its quality. But this traditional quadratic loss function is inadequate to assessing the quality and quality improvement since different processes have different sets of economic consequences on the manufacturing, Thereby, a flexible approach to the development of the loss function needs to be desired. In this paper, we introduce an easily understood loss function, based on reflection of probability density function of the normal distribution. That is, the Reflected Normal Loss function can be adapted to an asymmetric loss as well as to a symmetric loss around the target. We propose that, instead of the process variation, a new capability index, CpI using the Reflected Normal Loss Function that can accurately reflect the losses associated with the process and a new capability index CpI Is compared with the classical indices as $C_{p}$ , $C_{pk}$, $C_{pm}$ and $C_{pm}$ $^{+}$.>.+/./.

• The Journal of Korea Robotics Society
• /
• v.18 no.3
• /
• pp.330-336
• /
• 2023

In this paper, a novel line-based simultaneous localization and mapping (SLAM) using a loss function of vanishing point measurements is proposed. In general, the Huber norm is used as a loss function for point and line features in feature-based SLAM. The proposed loss function of vanishing point measurements is based on the unit sphere model. Because the point and line feature measurements define the reprojection error in the image plane as a residual, linear loss functions such as the Huber norm is used. However, the typical loss functions are not suitable for vanishing point measurements with unbounded problems. To tackle this problem, we propose a loss function for vanishing point measurements. The proposed loss function is based on unit sphere model. Finally, we prove the validity of the loss function for vanishing point through experiments on a public dataset.

• Journal of Applied Reliability
• /
• v.1 no.1
• /
• pp.35-46
• /
• 2001

Replacement policy of a degradation system is investigated by incorporating the loss function. Loss function is defined by the deviation of the value of quality characteristic from its target value, which determines the loss cost. Cost function is comprised of the inspection cost, replacement cost and loss cost. Two cost minimization problems are formulated : 1)determination of an optimal inspection period given the state for the replacement and 2)determination of an optimal state for replacement under fixed inspection period. Simulation analysis is performed to observe the variation of total cost with respect to the variation of the parameters of loss function and inspection cost, respectively As a result, parameters of loss function are seen to be the most sensitive to the total cost. On the contrary, inspection cost is observed to be insensitive. This study can be applied to the replacement policy of a degradation system which has to produce the quality critical product.

• Herbal Formula Science
• /
• v.11 no.1
• /
• pp.197-204
• /
• 2003

The skin is a barrier between the living organism and its environment, and this barrier function resides in the stratum corneum. The main function of the stratum corneum is to serve as a barrier preventing the penetration of irritants and transepidermal water loss(TEWL). The rate of transepidermal water loss is a convenient parameter for expressing barrier function. Impaired barrier function was manifested by a greatly increased rate of transepidermal water loss. In atopic dermatitis the rate of transepidermal water lossis greatly increased transepidermal water loss. Medication of Gagampalmultang restored to normal the abnormally high rates of transepidermal water loss in the 104 patients with atopic dermatitis. It specifically plays an important role in regulating barrier function.

• Communications for Statistical Applications and Methods
• /
• v.14 no.2
• /
• pp.389-399
• /
• 2007

In this paper, Bayes estimates for the parameters k, c and reliability function of the Burr type XII model based on a type II censored samples under asymmetric loss functions viz., LINEX and SQUAREX loss functions are obtained. An approximation based on the Laplace approximation method (Tierney and Kadane, 1986) is used for obtaining the Bayes estimators of the parameters and reliability function. In order to compare the Bayes estimators under squared error loss, LINEX and SQUAREX loss functions respectively and the maximum likelihood estimator of the parameters and reliability function, Monte Carlo simulations are used.

• Communications for Statistical Applications and Methods
• /
• v.7 no.3
• /
• pp.767-772
• /
• 2000

Zellner(1994) introduced the notion of a balanced loss function in the context of a general liner model to reflect both goodness of fit and precision of estimation. We study the perspective of unifying a variety of results both frequentist and Bayesian from Poisson distributions. We show that frequentist and Bayesian results for balanced loss follow from and also imply related results for quadratic loss functions reflecting only precision of estimation. Several examples are given for Poisson distribution.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.43 no.4
• /
• pp.107-115
• /
• 2020

Support vector regression (SVR) is devised to solve the regression problem by utilizing the excellent predictive power of Support Vector Machine. In particular, the ⲉ-insensitive loss function, which is a loss function often used in SVR, is a function thatdoes not generate penalties if the difference between the actual value and the estimated regression curve is within ⲉ. In most studies, the ⲉ-insensitive loss function is used symmetrically, and it is of interest to determine the value of ⲉ. In SVQR (Support Vector Quantile Regression), the asymmetry of the width of ⲉ and the slope of the penalty was controlled using the parameter p. However, the slope of the penalty is fixed according to the p value that determines the asymmetry of ⲉ. In this study, a new ε-insensitive loss function with p1 and p2 parameters was proposed. A new asymmetric SVR called GSVQR (Generalized Support Vector Quantile Regression) based on the new ε-insensitive loss function can control the asymmetry of the width of ⲉ and the slope of the penalty using the parameters p1 and p2, respectively. Moreover, the figures show that the asymmetry of the width of ⲉ and the slope of the penalty is controlled. Finally, through an experiment on a function, the accuracy of the existing symmetric Soft Margin, asymmetric SVQR, and asymmetric GSVQR was examined, and the characteristics of each were shown through figures.

• Journal of Korean Society for Quality Management
• /
• v.48 no.4
• /
• pp.535-552
• /
• 2020

Purpose: The main theme of this study is to derive a specific quality loss function with multiple characteristics according to the same analytical structure as the single characteristic quality loss function of Taguchi. In other words, it presents an analytical framework for measuring quality costs that can be controlled in practice. Methods: This study followed the analytical methodology through geometric, linear algebraic, and statistical approaches Results: The function suggested by this study is as follows; $$L(x_1,x_2,{\cdots},x_t)={\sum\limits_{i=1}^{t}}k_i\{x_i+{\sum\limits_{j=1}^{t}}\({\rho}_{ij}{\frac{d_i}{d_j}}\)x_j\}x_i$$ Conclusion: This paper derived the quality loss function with multiple quality characteristics to expand the usefulness of the Taguchi quality loss function. The function derived in this paper would be more meaningful to estimate quality costs under the practical situation and general structure with multiple quality characteristics than the function by linear algebraic approach in response surface analysis.

• Communications for Statistical Applications and Methods
• /
• v.21 no.3
• /
• pp.235-243
• /
• 2014

Constrained Bayesian estimates overcome the over shrinkness toward the mean which usual Bayes and empirical Bayes estimates produce by matching first and second empirical moments; subsequently, a constrained Bayes estimate is recommended to use in case the research objective is to produce a histogram of the estimates considering the location and dispersion. The well-known squared error loss function exclusively emphasizes the precision of estimation and may lead to biased estimators. Thus, the balanced loss function is suggested to reflect both goodness of fit and precision of estimation. In insurance pricing, the accurate location estimates of risk and also dispersion estimates of each risk group should be considered under proper loss function. In this paper, by applying these two ideas, the benefit of the constrained Bayes estimates and balanced loss function will be discussed; in addition, application effectiveness will be proved through an analysis of real insurance accident data.