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GGT-B; Washington, DC) Multivariate exponential families and the Taguchi loss function. ... We use information theory to define a multivariate loss function based on a divergence measure between two probability distribu- tions that belong to the multivariate exponential family. ...
Summary: “Previous results by the authors, regarding the distri- bution of maxima, and linear functions of dependent random variables arising in the context of Taguchi loss functions, are ex- tended. ... Summary: “In linear and nonlinear (curved) exponential families we present a generalization of the intrinsic and parameter effect curvatures of Bates and Watts (1980). ...
Klugman and Rahul Parsa, Fitting bivariate loss distributions with copulas (139-148); Moshe Arye Milevsky, Martingales, scale functions and stochastic life annuities: a note (149-154). ... Makov, Credibility evaluation for the exponential dispersion family (23-29); Michel Denuit, Claude Lefevre and M’hamed Mesfioui, A class of bivariate stochastic orderings, with applications in actuarial ...
The copula functions have been used to construct a multivariate model for mixed responses. ... We adapted the generalized distance approach to determine settings of the factors that simultaneously optimized the mean of continuous responses and desired cumulative categories of the ordinal responses ... They assume all margin distributions are the same and the joint distribution of responses are available and belong to the multivariate exponential family. ...doi:10.2991/jsta.d.190701.001 fatcat:j6brlvp5ivg3thauzso2iethjy
squared error loss. ... The R.S.L. of this rule and other similar truncated rules are calculated in terms of the R.S.L. of the un- truncated version and the incomplete gamma function. ...
This context is focused on the management of uncertainty, particularly based on the Taguchi worldview on robust design and robust optimization methods in the class of dual response methodology when simulation ... At the end, while both trends and gaps in the research field are highlighted, some suggestions for future research are directed. ... Ismail, and N. Ale Ebrahim, "Recent developments in metamodel based robust black-box simulation optimization: An overview," Decision Science Letters, vol. 8, no. 1, pp. 17-44, 2019. ...doi:10.6084/m9.figshare.6466625 fatcat:va7fpxohdvgn7o4boceztyqupe
For = 1 and = 2 respectively the exponential and Gaussian correlation function is made. ... For instance, the general exponential correlation function is defined as below: , ( , ) = ∏ exp (− | − | ) =1 (19) where is dimension of input variables, and determine the smoothness of the correlation ...doi:10.5267/j.dsl.2018.5.004 fatcat:j5ihfxwnlfesbcsuyyli622b44
In this package there are functions to compute the density function, the distribution function and the quantiles from an exponential power distribution and to generate pseudo-random numbers from the same ... Moreover, methods concerning the estimation of the distribution parameters are described and implemented. ... Acknowledgments The authors are grateful to two anonymous referees for thorough and constructive comments which greatly improved this paper. ...doi:10.18637/jss.v012.i04 fatcat:vhdzylsyrnbm5jdsckmk6mo4ui
The novel contribution here is an industrial case study, applying the combination of ACT and Taguchi Methods to DC-Directory, a product from Data Connection Ltd (DCL). ... Taguchi Methods were found to be useful for modelling and configuring DC- Directory, making them a valuable addition to the techniques available to system administrators and developers. ... Andrew Lang 14 This is the loss function suggested by Taguchi. ...arXiv:1006.5804v1 fatcat:s2hegcz2lfblfmtapc4skwzgam
Handbook of Statistics
However, we also mention the case of a stochastic simulation, and examples of both cases are discussed. ... We provide an overview of the general strategy and discuss applications in electrical engineering, chemical engineering, mechanical engineering, and dynamic programming. ... The "exponential" correlation function has ρ j = 1 for all j and is the product of Ornstein-Uhlenbeck processes. ...doi:10.1016/s0169-7161(03)22009-5 fatcat:32x27g76sneaxix2sxhog3joty
These opinions do not represent positions of the reviewer's organization and may not reflect those of the editors or the sponsoring societies. ... Listed prices reflect information provided by the publisher and may not be current. ... BOOK REVIEWS Nature-Inspired Methods in Chemometrics: Genetic Algorithms and Artificial Neural Networks, edited by Riccardo LEARDI, Amsterdam: Elsevier, 2003, ISBN 0-444-51350-7, xviii + 383 pp., $240.00 ...doi:10.1198/tech.2005.s824 fatcat:y6cla6trlbes7ojnfvqdordmni
This paper considers a stochastic approximation algorithm for estimating the controllable input parameter within a desired accuracy, given a target value for the performance function. ... Finally, the mean time to failure (MTTF) of a reliability subsystem is computed and compared with its known analytical MTTF value for validation purposes. ... Below the lower limit, the product is rejected; above the upper limit, the product must be reworked. The parabolic curve shown in Figure 2 represents the Taguchi loss function. ...doi:10.1080/15502287.2012.756957 fatcat:lpeqdmyfxbae3f5mck5ypw4uhu
Nanoindentation involves probing a hard diamond tip into a material, where the load and the displacement experienced by the tip is recorded continuously. ... This load-displacement data is a direct function of material's innate stress-strain behavior. ... On the other hand, RBF provides the ability to approximate a function with high fidelity in between the known values in a multivariable parameter space. ...arXiv:1612.03247v1 fatcat:eporh4wkkbh2xi2byhygbrwdum
The available process capability indices should therefore be abandoned and replaced by procedures that are normative, and also proactive with respect to both, prediction and control. ... They have been developed under the restrictive assumption of process stability, and the procedures for using them are based on ad hoc rules. ... Indeed Professor Dey considers several, to include non-symmetric, logistic, symmetric stable, and the exponential power family. ...doi:10.1007/bf02565102 fatcat:rixae5uzjjfq3oxiva6d2aydse
We formalize our goal as optimizing the multivariate value-at-risk (MVaR), a risk measure of the uncertain objectives. ... Empirically, we find that our approach significantly outperforms alternative methods and efficiently identifies optimal robust designs that will satisfy specifications across multiple metrics with high ... Acknowledgements We thank Ben Letham, David Eriksson, James Wilson, and Martin Jørgensen, as well as the members of the Oxford Machine Learning Research Group, for providing insightful feedback. ...arXiv:2202.07549v2 fatcat:kvljtboc5fhgdemlffjgxgc5l4
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