• Title/Summary/Keyword: assumptions

Search Result 2,205, Processing Time 0.026 seconds

Two tests using more assumptions but lower power

  • Sang Kyu Lee;Hyoung-Moon Kim
    • Communications for Statistical Applications and Methods
    • /
    • v.30 no.1
    • /
    • pp.109-117
    • /
    • 2023
  • Intuitively, a test with more assumptions has greater power than a test with fewer assumptions. This kind of examples are abundant in the nonparametric tests vs corresponding parametric ones. In general, the nonparametric tests are less efficient in terms of asymptotic relative efficiency (ARE) compared to corresponding parametric tests (Daniel, 1990). However, this is not always true. To test equal means under independent normal samples, the usual test involves using the t-distribution with the pooled estimator of the common variance. Adding the assumption of equal sample size, we may derive another test. In this case, two tests using more assumptions were performed for univariate (multivariate) cases. For these examples, it was found that the power function of a test with more assumptions is less than or equal to that of a test with fewer assumptions. This finding can be used as an expository example in master's mathematical statistics courses.

Effects of numerical modeling simplification on seismic design of buildings

  • Raheem, Shehata E Abdel;Omar, Mohamed;Zaher, Ahmed K Abdel;Taha, Ahmed M
    • Coupled systems mechanics
    • /
    • v.7 no.6
    • /
    • pp.731-753
    • /
    • 2018
  • The recent seismic events have led to concerns on safety and vulnerability of Reinforced Concrete Moment Resisting Frame "RC-MRF" buildings. The seismic design demands are greatly dependent on the computational tools, the inherent assumptions and approximations introduced in the modeling process. Thus, it is essential to assess the relative importance of implementing different modeling approaches and investigate the computed response sensitivity to the corresponding modeling assumptions. Many parameters and assumptions are to be justified for generation effective and accurate structural models of RC-MRF buildings to simulate the lateral response and evaluate seismic design demands. So, the present study aims to develop reliable finite element model through many refinements in modeling the various structural components. The effect of finite element modeling assumptions, analysis methods and code provisions on seismic response demands for the structural design of RC-MRF buildings are investigated. where, a series of three-dimensional finite element models were created to study various approaches to quantitatively improve the accuracy of FE models of symmetric buildings located in active seismic zones. It is shown from results of the comparative analyses that the use of a calibrated frame model which was made up of line elements featuring rigid offsets manages to provide estimates that match best with estimates obtained from a much more rigorous modeling approach involving the use of shell elements.

Study on the Analysis of Orthotropic Thin Plates and Orthotropic Thick Plates (직교이방성 박판 및 후판의 해석연구)

  • 박원태;최재진
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.4 no.2
    • /
    • pp.76-80
    • /
    • 2003
  • In this study, it is presented analysis results of bending problems in the orthotropic thick plates and the orthotropic thin plates. Finite element method in this analysis was used. Both Kirchoffs assumptions and Mindlin assumptions are used as the basic governing equations of bending problems in the orthotropic plates. The analysis results are compared between the orthotropic thick plates and the orthotropic thin plates for the variations of thickness-width ratios.

  • PDF

The Cost Impact of Incorrect Assumptions in a Supply Chain

  • Kim, Heung-Kyu
    • Management Science and Financial Engineering
    • /
    • v.10 no.2
    • /
    • pp.29-51
    • /
    • 2004
  • In this paper, the cost impact of incorrect assumptions about the demand process in a supply chain in which there are two participants, a retailer and a manufacturer, is considered. When participants in the supply chain do not notice serial correlation in the demand process, they would turn to a simple inventory model based on an i.i.d. demand assumption. A mathematical model that allows us to quantify the cost incurred by each participant in the supply chain, when they implement inventory policies based on correct or incorrect assumptions about the demand process, is developed. This model enables us to identify how much it differs from the optimal costs.

Future Directions and Perspectives for Performance Assessment in Mathematics (수학과 학업성취도 평가를 위한 수행평가의 과제와 전망)

  • 성태제;권오남
    • School Mathematics
    • /
    • v.1 no.1
    • /
    • pp.217-234
    • /
    • 1999
  • The first part of this paper examines the assumptions underlying traditional types of standardized testing compared with assumptions underlying innovative types of performance assessment. The second part focuses on directions for the future. The third part gives examples from closed related projects which were designed to find practical ways to implement recommendations.

  • PDF

A Study on the Analysis of Anisotropic Thin and Thick Shells (비등방성 얇은 쉘 및 두꺼운 쉘의 해석연구)

  • Park Weon-Tae
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.6 no.6
    • /
    • pp.525-530
    • /
    • 2005
  • In this study, it is presented analysis results of bending problems in the anisotropic thick shell and the anisotropic thin shell bending problems. In the numerical analysis of various mechanical problems involving complex partial differential equations, finite element method is used. Both Kirchoffs assumptions and Mindlin assumptions are used as the basic governing equations of bending problems in the anisotropic shells. The analysis results are compared between the anisotropic thick shells and the anisotropic thin shells for the various width-thickness ratios. The numerical method of this study will be contributed not only to analysis the bending behavior of anisotropic shells but also to design the anisotropic shells.

  • PDF

Robustness of model averaging methods for the violation of standard linear regression assumptions

  • Lee, Yongsu;Song, Juwon
    • Communications for Statistical Applications and Methods
    • /
    • v.28 no.2
    • /
    • pp.189-204
    • /
    • 2021
  • In a regression analysis, a single best model is usually selected among several candidate models. However, it is often useful to combine several candidate models to achieve better performance, especially, in the prediction viewpoint. Model combining methods such as stacking and Bayesian model averaging (BMA) have been suggested from the perspective of averaging candidate models. When the candidate models include a true model, it is expected that BMA generally gives better performance than stacking. On the other hand, when candidate models do not include the true model, it is known that stacking outperforms BMA. Since stacking and BMA approaches have different properties, it is difficult to determine which method is more appropriate under other situations. In particular, it is not easy to find research papers that compare stacking and BMA when regression model assumptions are violated. Therefore, in the paper, we compare the performance among model averaging methods as well as a single best model in the linear regression analysis when standard linear regression assumptions are violated. Simulations were conducted to compare model averaging methods with the linear regression when data include outliers and data do not include them. We also compared them when data include errors from a non-normal distribution. The model averaging methods were applied to the water pollution data, which have a strong multicollinearity among variables. Simulation studies showed that the stacking method tends to give better performance than BMA or standard linear regression analysis (including the stepwise selection method) in the sense of risks (see (3.1)) or prediction error (see (3.2)) when typical linear regression assumptions are violated.