• Title/Summary/Keyword: assumptions

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An Empirical Study on Dimension Reduction

  • Suh, Changhee;Lee, Hakbae
    • Journal of the Korean Data Analysis Society
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    • v.20 no.6
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    • pp.2733-2746
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    • 2018
  • The two inverse regression estimation methods, SIR and SAVE to estimate the central space are computationally easy and are widely used. However, SIR and SAVE may have poor performance in finite samples and need strong assumptions (linearity and/or constant covariance conditions) on predictors. The two non-parametric estimation methods, MAVE and dMAVE have much better performance for finite samples than SIR and SAVE. MAVE and dMAVE need no strong requirements on predictors or on the response variable. MAVE is focused on estimating the central mean subspace, but dMAVE is to estimate the central space. This paper explores and compares four methods to explain the dimension reduction. Each algorithm of these four methods is reviewed. Empirical study for simulated data shows that MAVE and dMAVE has relatively better performance than SIR and SAVE, regardless of not only different models but also different distributional assumptions of predictors. However, real data example with the binary response demonstrates that SAVE is better than other methods.

Introduction to Mediation Analysis and Examples of Its Application to Real-world Data

  • Jung, Sun Jae
    • Journal of Preventive Medicine and Public Health
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    • v.54 no.3
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    • pp.166-172
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    • 2021
  • Traditional epidemiological assessments, which mainly focused on evaluating the statistical association between two major components-the exposure and outcome-have recently evolved to ascertain the in-between process, which can explain the underlying causal pathway. Mediation analysis has emerged as a compelling method to disentangle the complex nature of these pathways. The statistical method of mediation analysis has evolved from simple regression analysis to causal mediation analysis, and each amendment refined the underlying mathematical theory and required assumptions. This short guide will introduce the basic statistical framework and assumptions of both traditional and modern mediation analyses, providing examples conducted with real-world data.

A Survey of Public-Key Cryptography over Non-Abelian Groups

  • Lanel, G.H.J.;Jinasena, T.M.K.K.;Welihinda, B.A.K.
    • International Journal of Computer Science & Network Security
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    • v.21 no.4
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    • pp.289-300
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    • 2021
  • Non-abelian group based Cryptography is a field which has become a latest trend in research due to increasing vulnerabilities associated with the abelian group based cryptosystems which are in use at present and the interesting algebraic properties associated that can be thought to provide higher security. When developing cryptographic primitives based on non-abelian groups, the researchers have tried to extend the similar layouts associated with the traditional underlying mathematical problems and assumptions by almost mimicking their operations which is fascinating even to observe. This survey contributes in highlighting the different analogous extensions of traditional assumptions presented by various authors and a set of open problems. Further, suggestions to apply the Hamiltonian Cycle/Path Problem in a similar direction is presented.

Generalized Bayes estimation for a SAR model with linear restrictions binding the coefficients

  • Chaturvedi, Anoop;Mishra, Sandeep
    • Communications for Statistical Applications and Methods
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    • v.28 no.4
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    • pp.315-327
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    • 2021
  • The Spatial Autoregressive (SAR) models have drawn considerable attention in recent econometrics literature because of their capability to model the spatial spill overs in a feasible way. While considering the Bayesian analysis of these models, one may face the problem of lack of robustness with respect to underlying prior assumptions. The generalized Bayes estimators provide a viable alternative to incorporate prior belief and are more robust with respect to underlying prior assumptions. The present paper considers the SAR model with a set of linear restrictions binding the regression coefficients and derives restricted generalized Bayes estimator for the coefficients vector. The minimaxity of the restricted generalized Bayes estimator has been established. Using a simulation study, it has been demonstrated that the estimator dominates the restricted least squares as well as restricted Stein rule estimators.

Contribution of Reinforced Concrete Floor Slabs to Lateral Behavior of Tall Buildings

  • Rehmanjee, Yasmin;Leslie, Benjamin;Lamianski, Dmitri;Chafart, Manuel
    • International Journal of High-Rise Buildings
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    • v.11 no.1
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    • pp.25-29
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    • 2022
  • This paper focuses on how the coupling of the columns and walls through the structural slab contributes to the overall stiffness and strength of lateral systems. The rationale and procedures behind the design approach, which may offer a shift from more conventional assumptions made regarding compatibility and connectivity of gravity and lateral structural systems, will be introduced. The impacts on serviceability and strength design will be discussed, and observations on key design and analysis approaches will be featured. Mass and stiffness assumptions will also be reviewed. A case study on the topic will be presented describing implementation of slab coupling into engineering of a building project.

LMI-based $H_\infty$ Robust Control of Asymmetric Rotor-magnetic Bearing System (비대칭 로터-자기베어링 시스템의 LMI에 기초한 $H_\infty$ 강건제어)

  • 강호식;송오섭
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.13 no.3
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    • pp.172-179
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    • 2003
  • Linear matrix Inequality based $H_\infty$ robust controller is designed to control the motion of a 4-axis unbalanced rigid asymmetric rotor supported and controlled by two active magnetic bearings in this paper. To this end, the equations of motion of the system are derived via Hamilton's variational principle and transformed to a state-space form for the standard $H_\infty$ control problem. LMI-based controller, which does not require additional assumptions beyond the usual stabilizability and detectability assumptions, is designed based upon the pole place weighting function and loopshaping technique. The obtained results are compared with those reported in the available literature and the efficiency of the proposed LMI-based $H_\infty$ control is revealed.

On the Srivastava's Theorem for the search design.

  • Um, Jung-Koog
    • Journal of the Korean Statistical Society
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    • v.9 no.2
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    • pp.126-134
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    • 1980
  • In this paper, Srivastava's Theorem for the search design is considered, with additional assumptions, to the $3^n$ parallel flats fractions. It is also expressed in terms of ACPM.

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