• Structural Engineering and Mechanics
• /
• v.92 no.1
• /
• pp.111-120
• /
• 2024

Sampling methods are powerful approaches to solving the problems of structural reliability analysis and estimating the failure probability of structures. In this paper, a new sampling method is proposed offering lower variance and lower computational cost for complex and high-dimensional problems. The method is called Optimal Latinized partially stratified sampling (OLPSS) as it is based upon the Latinized Partially Stratified Sampling (LPSS) which itself is based on merging Stratified Sampling (SS) and Latin Hypercube Sampling (LHS) algorithms. While LPSS has a low variance, it may suffer from a lack of good space-filling of its generated samples in some cases. In the OLPSS, this issue has been resolved by employing a new columnwise-pairwise exchange optimization procedure for sample generation. The efficiency of the OLPSS has been tested and reported under several benchmark mathematical functions and structural examples including structures with a large number of variables (e.g., a structure with 67 variables). The proposed method provides highly accurate estimates of the failure probability of structures with a significantly lower variance relative to the Monte Carlo simulations, Latin Hypercube, and standard LPSS.

• Asian-Australasian Journal of Animal Sciences
• /
• v.24 no.3
• /
• pp.330-335
• /
• 2011

The mode of inheritance of total milk yield and its genetic parameters were investigated in Churra dairy sheep through segregation analyses using a Monte Carlo Markov Chains (MCMC) method. Data which consisted of 7,126 lactations belonging to 5,154 ewes were collected between 1999 and 2002 from 15 Spanish Churra dairy flocks. A postulated major gene was assumed to be additive and priors used for variance components were uniform. Based on 50 000 Gibbs samples from ten replicates chains of 100,000 cycles, the estimated marginal posterior means${\pm}$posterior standard deviations of variance components of milk yield were $23.17{\pm}18.42$, $65.20{\pm}25.05$, $120.40{\pm}42.12$ and $420.83{\pm}40.26$ for major gene variance ($\sigma_G^2$), polygenic variance ($\sigma_u^2$), permanent environmental variance ($\sigma_{pe}^2$) and error variance ($\sigma_e^2$), respectively. The results of this study showed the postulated major locus was not significant, and the 95% highest posterior density regions ($HPDs_{95%}$) of most major gene parameters included 0, and particularly for the major gene variance. The estimated transmission probabilities for the 95% highest posterior density regions ($HPDs_{95%}$) were overlapped. These results indicated that segregation of a major gene was unlikely and that the mode of inheritance of total milk yield in Churra dairy sheep is purely polygenic. Based on 50,000 Gibbs samples from ten replicates chains of 100,000 cycles, the estimated polygenic heritability and repeatability were $h^2=0.20{\pm}0.05$ and r=$0.34{\pm}0.06$, respectively.

• Communications for Statistical Applications and Methods
• /
• v.12 no.1
• /
• pp.181-189
• /
• 2005

This paper suggest a method of inclusion probability proportional to size sampling that provides a non-negative and stable variance estimator. The sampling procedure is quite simple and flexible since a sampling design is easily obtained using mathematical programming. This scheme appears to be preferable to Nigam, Kumar and Gupta's (1984) method which uses a balanced incomplete block designs. A comparison is made with their method through an example in the literature.

• Proceedings of the IEEK Conference
• /
• 2002.07b
• /
• pp.1153-1156
• /
• 2002

In this parer, a high quality mesh generation method by using interval arithmetic is proposed. In the proposed method, the variance of a tangent vector at the point is considered by the automatic differentiation. From the variance, sampling points on the surface are judged whether it is adequate or not, which is calculated by the interval arithmetic. Then Delaunay triangulation is performed to the obtained sampling points, and a set of meshes is generated. The proposed method is hard to overlook the local variation of surfaces.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2001.04a
• /
• pp.1008-1011
• /
• 2001

The purpose of this paper is to evaluate the chip breakability during turning using the experimental equation, which is developed by an orthogonal array method. The chip breaking index(CB), non-dimensional parameter is used in the evaluation of chip breakability. The analysis of variance(ANOVA)-test has been used to check the significance of cutting parameters. And using the result of ANOVA-test, the experimental equation of chip breakability, which consists of significant cutting parameters, has been developed.

• Journal of applied mathematics & informatics
• /
• v.26 no.5_6
• /
• pp.1169-1183
• /
• 2008

In this paper, a method to find the weighted possibilistic variance and moments about the mean value of fuzzy numbers via applying a difuzzification using minimizer of the weighted distance between two fuzzy numbers is introduced. In this way, we obtain the nearest weighted point with respect to a fuzzy number, this main result is a new and interesting alternative justification to define of weighted mean of a fuzzy number. Considering this point and the weighted distance quantity, we introduce the weighted possibilistic mean (WPM) value and the weighted possibilistic variance(WPV) of fuzzy numbers. This paper shows that WPM is the nearest weighted point to fuzzy number and the WPV of fuzzy number is preserved more properties of variance in probability theory so that it can simply introduce the possibilistic moments about the mean of fuzzy numbers without problem. The moments of fuzzy numbers play an important role to estimate of parameters, skewness, kurtosis in many of fuzzy times series models.

• Asian-Australasian Journal of Animal Sciences
• /
• v.13 no.3
• /
• pp.413-422
• /
• 2000

In the class of models which include random effects, the variance component estimates are important to obtain accurate predictors and estimators. Variance component estimation is straightforward for balanced data but not for unbalanced data. Since orthogonality among factors is absent in unbalanced data, various methods for variance component estimation are available. REML estimation is the most widely used method in animal breeding because of its attractive statistical properties. Recently, Bayesian approach became feasible through Markov Chain Monte Carlo methods with increasingly powerful computers. Furthermore, advances in variance component estimation with complicated models such as generalized linear mixed models enabled animal breeders to analyze non-normal data.

• Journal of Institute of Control, Robotics and Systems
• /
• v.8 no.3
• /
• pp.275-280
• /
• 2002

A new algorithm for gradual scene change detection in MPEG based frame sequences is proposed in this paper. The proposed algorithm is based on the fact that most of gradual curves can be characterized by variance distributions of edge information in the frame sequences. Average edge frame sequences are obtained by performing "sober" edge detection. Features are extracted by comparing variances with those of local blocks in the average edge frames. Those features are further processed by the opening operation to obtain smoothing variance curves. The lowest variance in the local frame sequences is chosen as a gradual detection point. Experimental results show that the proposed method provides 85% precision and 86% recall rate fur gradual scene changes.

• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• v.20 no.2
• /
• pp.123-135
• /
• 2016

This article deals with the pricing of Asian options under a constant elasticity of variance (CEV) model as well as a stochastic elasticity of variance (SEV) model. The CEV and SEV models are underlying asset price models proposed to overcome shortcomings of the constant volatility model. In particular, the SEV model is attractive because it can characterize the feature of volatility in risky situation such as the global financial crisis both quantitatively and qualitatively. We use an asymptotic expansion method to approximate the no-arbitrage price of an arithmetic average Asian option under both CEV and SEV models. Subsequently, the zero and non-zero constant leverage effects as well as stochastic leverage effects are compared with each other. Lastly, we investigate the SEV correction effects to the CEV model for the price of Asian options.

• Communications for Statistical Applications and Methods
• /
• v.25 no.3
• /
• pp.275-282
• /
• 2018

This paper discusses the use of projections for the sums of squares in the analyses of variance for two-way nested design data. The model for this data is assumed to only have random effects. Two different sizes of experimental units are required for a given experimental situation, since nesting is assumed to occur both in the treatment structure and in the design structure. So, variance components are coming from the sources of random effects of treatment factors and error terms in different sizes of experimental units. The model for this type of experimental situation is a random effects model with more than one error terms and therefore estimation of variance components are concerned. A projection method is used for the calculation of sums of squares due to random components. Squared distances of projections instead of using the usual reductions in sums of squares that show how to use projections to estimate the variance components associated with the random components in the assumed model. Expectations of quadratic forms are obtained by the Hartley's synthesis as a means of calculation.