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Relevant bibliographies by topics / Parametric and nonparametric tests

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Academic literature on the topic 'Parametric and nonparametric tests'

Author: Grafiati

Published: 4 June 2021

Last updated: 3 February 2022

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Journal articles on the topic "Parametric and nonparametric tests"

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HARWELL, MICHAEL R. "Choosing Between Parametric and Nonparametric Tests." Journal of Counseling & Development 67, no. 1 (September 1988): 35–38. http://dx.doi.org/10.1002/j.1556-6676.1988.tb02007.x.

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Stojanović, Miodrag, Marija Andjelković - Apostolović, Zoran Milošević, and Aleksandra Ignjatović. "PARAMETRIC VERSUS NONPARAMETRIC TESTS IN BIOMEDICAL RESEARCH." Acta Medica Medianae 57, no. 2 (March 15, 2018): 75–80. http://dx.doi.org/10.5633/amm.2018.0212.

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Hunter, Michael A., and Richard B. May. "Some myths concerning parametric and nonparametric tests." Canadian Psychology/Psychologie canadienne 34, no. 4 (1993): 384–89. http://dx.doi.org/10.1037/h0078860.

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El-Shaarawi, A. H., and Eivind Damsleth. "PARAMETRIC AND NONPARAMETRIC TESTS FOR DEPENDENT DATA." Journal of the American Water Resources Association 24, no. 3 (June 1988): 513–19. http://dx.doi.org/10.1111/j.1752-1688.1988.tb00901.x.

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Cintra, Renato J., Alejandro C. Frery, and Abraão D. C. Nascimento. "Parametric and nonparametric tests for speckled imagery." Pattern Analysis and Applications 16, no. 2 (October 15, 2011): 141–61. http://dx.doi.org/10.1007/s10044-011-0249-3.

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Blanciforti, Laura A. "Consumer Demand Analysis According to GARP: Discussion." Northeastern Journal of Agricultural and Resource Economics 21, no. 2 (October 1992): 140–41. http://dx.doi.org/10.1017/s0899367x00002658.

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This paper explores the issue of the power of nonparametric tests to check for the consistency of data with utility maximization. Alston and Chalfant provide an excellent review of nonparametric approaches to consumer-demand analysis. They test for consistency, separability, and power. The authors address two important questions: First, how does one define power for nonparametric situations, and is that definition comparable to the parametric situation? Second, can the power of nonparametric tests be improved? The authors measure the statistical power of nonparametric methods using a parametric test, though they do not address whether it is legitimate to use parametric tests on nonparametric methods.

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Singhal, Richa, RakeshKumar Rana, and Pamila Dua. "Deciphering the dilemma of parametric and nonparametric tests." Journal of the Practice of Cardiovascular Sciences 2, no. 2 (2016): 95. http://dx.doi.org/10.4103/2395-5414.191521.

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Kahraman, Cengiz, Cafer Erhan Bozdag, Da Ruan, and Ahmet Fahri Özok. "Fuzzy sets approaches to statistical parametric and nonparametric tests." International Journal of Intelligent Systems 19, no. 11 (September 24, 2004): 1069–87. http://dx.doi.org/10.1002/int.20037.

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Emerson, Robert Wall. "Parametric Tests, Their Nonparametric Alternatives, and Degrees of Freedom." Journal of Visual Impairment & Blindness 110, no. 5 (September 2016): 377–80. http://dx.doi.org/10.1177/0145482x1611000511.

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Kitchen, Christina M. R. "Nonparametric vs Parametric Tests of Location in Biomedical Research." American Journal of Ophthalmology 147, no. 4 (April 2009): 571–72. http://dx.doi.org/10.1016/j.ajo.2008.06.031.

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Dissertations / Theses on the topic "Parametric and nonparametric tests"

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Wang, Sejong. "Three nonparametric specification tests for parametric regression models : the kernel estimation approach." Connect to resource, 1994. http://rave.ohiolink.edu/etdc/view.cgi?acc%5Fnum=osu1261492759.

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Chen, Andrew H. (Andrew Hwa-Fen). "Robustness of Parametric and Nonparametric Tests When Distances between Points Change on an Ordinal Measurement Scale." Thesis, University of North Texas, 1994. https://digital.library.unt.edu/ark:/67531/metadc278300/.

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The purpose of this research was to evaluate the effect on parametric and nonparametric tests using ordinal data when the distances between points changed on the measurement scale. The research examined the performance of Type I and Type II error rates using selected parametric and nonparametric tests.

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Shadat, Wasel Bin. "Specification testing of Garch regression models." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/specification-testing-of-garch-regression-models(56c218db-9b91-4d8c-bf26-8377ab185c71).html.

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This thesis analyses, derives and evaluates specification tests of Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) regression models, both univariate and multivariate. Of particular interest, in the first half of the thesis, is the derivation of robust test procedures designed to assess the Constant Conditional Correlation (CCC) assumption often employed in multivariate GARCH (MGARCH) models. New asymptotically valid conditional moment tests are proposed which are simple to construct, easily implementable following the full or partial Quasi Maximum Likelihood (QML) estimation and which are robust to non-normality. In doing so, a non-normality robust version of the Tse's (2000) LM test is provided. In addition, a new and easily programmable expressions of the expected Hessian matrix associated with the QMLE is obtained. The finite sample performances of these tests are investigated in an extensive Monte Carlo study, programmed in GAUSS.In the second half of the thesis, attention is devoted to nonparametric testing of GARCH regression models. First simultaneous consistent nonparametric tests of the conditional mean and conditional variance structure of univariate GARCH models are considered. The approach is developed from the Integrated Generalized Spectral (IGS) and Projected Integrated Conditional Moment (PICM) procedures proposed recently by Escanciano (2008 and 2009, respectively) for time series models. Extending Escanciano (2008), a new and simple wild bootstrap procedure is proposed to implement these tests. A Monte Carlo study compares the performance of these nonparametric tests and four parametric tests of nonlinearity and/or asymmetry under a wide range of alternatives. Although the proposed bootstrap scheme does not strictly satisfy the asymptotic requirements, the simulation results demonstrate its ability to control the size extremely well and therefore the power comparison seems justified. Furthermore, this suggests there may exist weaker conditions under which the tests are implementable. The simulation exercise also presents the new evidence of the effect of conditional mean misspecification on various parametric tests of conditional variance. The testing procedures are also illustrated with the help of the S&P 500 data. Finally the PICM and IGS approaches are extended to the MGARCH case. The procedure is illustrated with the help of a bivariate CCC-GARCH model, but can be generalized to other MGARCH specifications. Simulation exercise shows that these tests have satisfactory size and are robust to non-normality. The marginal mean and variance tests have excellent power; however the covariance marginal tests lack power for some alternatives.

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Georgii, Hellberg Kajsa-Lotta, and Andreas Estmark. "Fisher's Randomization Test versus Neyman's Average Treatment Test." Thesis, Uppsala universitet, Statistiska institutionen, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385069.

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The following essay describes and compares Fisher's Randomization Test and Neyman's average treatment test, with the intention of concluding an easily understood blueprint for the comprehension of the practical execution of the tests and the conditions surrounding them. Focus will also be directed towards the tests' different implications on statistical inference and how the design of a study in relation to assumptions affects the external validity of the results. The essay is structured so that firstly the tests are presented and evaluated, then their different advantages and limitations are put against each other before they are applied to a data set as a practical example. Lastly the results obtained from the data set are compared in the Discussion section. The example used in this paper, which compares cigarette consumption after having treated one group with nicotine patches and another with fake nicotine patches, shows a decrease in cigarette consumption for both tests. The tests differ however, as the result from the Neyman test can be made valid for the population of interest. Fisher's test on the other hand only identifies the effect derived from the sample, consequently the test cannot draw conclusions about the population of heavy smokers. In short, the findings of this paper suggests that a combined use of the two tests would be the most appropriate way to test for treatment effect. Firstly one could use the Fisher test to check if any effect at all exist in the experiment, and then one could use the Neyman test to compensate the findings of the Fisher test, by estimating an average treatment effect for example.

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Chroboček, Michal. "Případové studie pro statistickou analýzu dat." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-217911.

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This thesis deals with questions which are related to the creation of case studies for statistical data analysis using applied computer technology. The main aim is focused on showing the solution of statistical case studies in the field of electrical engineering. Solved case studies include task, exemplary solution and conclusion. Clarity of explained theory and the results understanding and interpretation is accentuated. This thesis can be used for practical education of applied statistical methods, it’s also supplemented with commented outputs from Minitab. Trial version of Minitab has been used for solution of case studies.

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Lopez, Gabriel E. "Detection and Classification of DIF Types Using Parametric and Nonparametric Methods: A comparison of the IRT-Likelihood Ratio Test, Crossing-SIBTEST, and Logistic Regression Procedures." Scholar Commons, 2012. http://scholarcommons.usf.edu/etd/4131.

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The purpose of this investigation was to compare the efficacy of three methods for detecting differential item functioning (DIF). The performance of the crossing simultaneous item bias test (CSIBTEST), the item response theory likelihood ratio test (IRT-LR), and logistic regression (LOGREG) was examined across a range of experimental conditions including different test lengths, sample sizes, DIF and differential test functioning (DTF) magnitudes, and mean differences in the underlying trait distributions of comparison groups, herein referred to as the reference and focal groups. In addition, each procedure was implemented using both an all-other anchor approach, in which the IRT-LR baseline model, CSIBEST matching subtest, and LOGREG trait estimate were based on all test items except for the one under study, and a constant anchor approach, in which the baseline model, matching subtest, and trait estimate were based on a predefined subset of DIF-free items. Response data for the reference and focal groups were generated using known item parameters based on the three-parameter logistic item response theory model (3-PLM). Various types of DIF were simulated by shifting the generating item parameters of select items to achieve desired DIF and DTF magnitudes based on the area between the groups' item response functions. Power, Type I error, and Type III error rates were computed for each experimental condition based on 100 replications and effects analyzed via ANOVA. Results indicated that the procedures varied in efficacy, with LOGREG when implemented using an all-other approach providing the best balance of power and Type I error rate. However, none of the procedures were effective at identifying the type of DIF that was simulated.

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Cícha, Martin. "Extrakce informací o pravděpodobnosti a riziku výnosů z cen opcí." Doctoral thesis, Vysoká škola ekonomická v Praze, 2004. http://www.nusl.cz/ntk/nusl-77098.

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The issue of forecasting the future price of risky financial assets has attracted academia and business practice since the inception of the stock exchange. Also due to the just finished financial crisis, which was the worst crisis since the Great Depression, it is clear that research in this area has not been finished yet. On the contrary, new challenges have been raised. The main goal of the thesis is the demonstration of the significant information potential which is hidden in option market prices. These prices contain informations on probability distribution of the underlying asset returns and the risk connected with these returns. Other objectives of the thesis are the forecast of the underlying asset price distribution using parametric and nonparametric estimates, the improvement of this forecast using the utility function of the representative investor, the description of the current market sentiment and the determination of the risk premium, especially the risk premium on Czech market. The thesis deals with the forecast of the underlying asset price probability distribution implied by the current option market prices using parametric and nonparametric estimates. The resulting distribution is described by the moment characteristics which represent a valuable tool for analyzing the current market sentiment. According to the theory, the probability distribution of the underlying asset price implied by option prices is risk neutral, i.e. it applies only to risk neutral investors. The theory further implies that the distribution of real world can be derived from the risk neutral distribution using utility function of the representative investor. The inclusion of a utility function of representative investor improves the forecast of the underlying asset price distribution. Three different utility functions of traditional risk theory are used in the thesis. These functions range from the simple power function to the general function of hyperbolic absolute risk aversion (HARA). Further, Friedman-Savage utility function is used. This function allows both a risk averse investor and a risk loving investor. The thesis also answers the question: Are the current asset prices at so high level that the purchase of the asset means a gamble? The risk premium associated with investing in the risky asset is derived in the thesis. The risk premium can be understood as the premium demanded by investors for investment in a risky asset against the investment in a riskless asset. All the theoretical methods introduced in the thesis are demonstrated on real data coming from two different markets. Developing market is represented by shares of CEZ and developed market is represented by S&P 500 futures. The thesis deals with demonstrations in single point in time as well as in available history of the data. The forecasts of the underlying asset price distribution and the relating risk premium are constructed in the available data history. The goals and the objectives of the thesis have been achieved. The contribution of the thesis is the development of parametric and nonparametric methodology for estimating the underlying asset price probability distribution implied by the option market prices so that the nature of the particular market and instrument is captured. The further contribution of the thesis is the construction of the forecasts of the underlying asset price distribution and the construction of the market sentiment in the available history of data. The contribution of the thesis is also the construction of the market risk premium in the available history and the establishment of the hypothesis that the markets gamble before the crisis.

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Dong, Lei. "Nonparametric tests for longitudinal data." Manhattan, Kan. : Kansas State University, 2009. http://hdl.handle.net/2097/2295.

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Millen, Brian A. "Nonparametric tests for umbrella alternatives /." The Ohio State University, 2001. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488205318508038.

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Ho, Pak-kei. "Parametric and non-parametric inference for Geometric Process." Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B31483859.

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Books on the topic "Parametric and nonparametric tests"

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Hart, Jeffrey D. Nonparametric smoothing and lack-of-fit tests. New York: Springer, 1997.

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Alvo, Mayer, and Philip L. H. Yu. A Parametric Approach to Nonparametric Statistics. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94153-0.

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Mo, Moxiu. Nonparametric estimation by (parametric) linear regression. Toronto: University of Toronto, Dept. of Statistics, 1991.

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Dickhaus, Thorsten. Theory of Nonparametric Tests. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76315-6.

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Handbook of parametric and nonparametric statistical procedures. 4th ed. Boca Raton: Chapman & Hall/CRC, 2007.

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Sheskin, David. Handbook of parametric and nonparametric statistical procedures. 2nd ed. Boca Raton: Chapman & Hall/CRC, 2000.

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Handbook of parametric and nonparametric statistical procedures. 3rd ed. Boca Raton: Chapman & Hall/CRC, 2004.

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Handbook of parametric and nonparametric statistical procedures. Boca Raton, Fla: CRC Press, 1997.

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Handbook of parametric and nonparametric statistical procedures. 5th ed. Boca Raton: CRC Press, 2011.

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Sheskin, David. Handbook of parametric and nonparametric statistical procedures. 3rd ed. Boca Raton: Chapman & Hall/CRC, 2004.

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Book chapters on the topic "Parametric and nonparametric tests"

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Noether, Gottfried E. "Nonparametric and Parametric Tests." In Introduction to Statistics, 129–42. New York, NY: Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4612-0943-0_8.

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Sheskin, David J. "Parametric Versus Nonparametric Tests." In International Encyclopedia of Statistical Science, 1051–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_440.

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Alvo, Mayer, and Philip L. H. Yu. "Optimal Rank Tests." In A Parametric Approach to Nonparametric Statistics, 163–86. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94153-0_8.

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Alvo, Mayer, and Philip L. H. Yu. "Smooth Goodness of Fit Tests." In A Parametric Approach to Nonparametric Statistics, 63–89. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94153-0_4.

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Alvo, Mayer, and Philip L. H. Yu. "Tests for Trend and Association." In A Parametric Approach to Nonparametric Statistics, 137–61. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94153-0_7.

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Bhattacharya, Rabi, Lizhen Lin, and Victor Patrangenaru. "Tests in Parametric and Nonparametric Models." In Springer Texts in Statistics, 203–56. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-4032-5_8.

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Arboretti, Rosa, Riccardo Ceccato, and Luigi Salmaso. "Nonparametric methods for stratified C-sample designs: a case study." In Proceedings e report, 17–22. Florence: Firenze University Press, 2021. http://dx.doi.org/10.36253/978-88-5518-304-8.05.

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Several parametric and nonparametric methods have been proposed to deal with stratified C-sample problems where the main interest lies in evaluating the presence of a certain treatment effect, but the strata effects cannot be overlooked. Stratified scenarios can be found in several different fields. In this paper we focus on a particular case study from the field of education, addressing a typical stochastic ordering problem in the presence of stratification. We are interested in assessing how the performance of students from different degree programs at the University of Padova change, in terms of university credits and grades, when compared with their entry test results. To address this problem, we propose an extension of the Non-Parametric Combination (NPC) methodology, a permutation-based technique (see Pesarin and Salmaso, 2010), as a valuable tool to improve the data analytics for monitoring University students’ careers at the School of Engineering of the University of Padova. This new procedure indeed allows us to assess the efficacy of the University of Padova’s entry tests in evaluating and selecting future students.

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Yadav, Shakti Kumar, Sompal Singh, and Ruchika Gupta. "Nonparametric Tests." In Biomedical Statistics, 133–44. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9294-9_17.

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Pace, Larry. "Nonparametric Tests." In Beginning R, 229–46. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-4555-1_16.

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"Parametric versus Nonparametric Tests." In An Introduction to Statistical Analysis in Research, 191–94. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2017. http://dx.doi.org/10.1002/9781119454205.ch4.

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Conference papers on the topic "Parametric and nonparametric tests"

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Hu, Xiao, Neil Eklund, and Kai Goebel. "A Data Fusion Approach for Aircraft Engine Fault Diagnostics." In ASME Turbo Expo 2007: Power for Land, Sea, and Air. ASMEDC, 2007. http://dx.doi.org/10.1115/gt2007-27941.

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Accurate and timely detection and identification of aircraft engine faults is critical to keeping the engine and aircraft in a healthy operating state. Early detection of faults increases the window of opportunity to schedule maintenance actions both at a convenient time and before the fault progresses and causes equipment downtime and secondary damage to the system. Typically, diagnostic models are built using parametric sensor data to infer the state of the system. However, recording and collecting this data is costly, and it is generally limited to a few snapshots over the course of a flight for commercial aircraft. Another way to recognize faults is through the use of built-in tests that produce error log messages. These tests produce data that is less information rich, but provide insight over the course of the entire flight. Each data source provides a different perspective of the state of the system. Therefore, it may be advantageous to combine information from parametric and nonparametric sources to improve fault diagnosis in terms of accuracy and timeliness of diagnosis. In this paper, we investigate integrating parametric sensor data and nonparametric information in fault diagnosis, specifically the way to parameterize nonparametric information for use in diagnostic models that accept only parametric data (e.g., most machine learning techniques). Results from high bypass commercial engines are presented.

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Dhupia, Jaspreet, Bartosz Powalka, A. Galip Ulsoy, and Reuven Katz. "Experimental Identification of the Nonlinear Parameters of an Industrial Translational Guide." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-14450.

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Prediction of machine dynamics at the design stage is a challenge due to lack of adequate methods for identifying and handling the nonlinearities in the machine joints, which appear as the nonlinear restoring force function of relative displacement and relative velocity across the joint. This paper discusses identification of such a nonlinear restoring force function for an industrial translational guide for use with the Nonlinear Receptance Coupling Approach (NLRCA) for evaluating machine dynamic characteristics. Translational guides are among the most commonly used joints in machine tools. Both a parametric and nonparametric technique has been employed to identify the nonlinearities. A novel parametric model based on Hertzian contact mechanics has been derived for the translational guide. This model includes the effect of joint geometry, material properties and preload. A nonparametric method based on two-dimensional Chebyshev polynomials is also used. The models derived from the two techniques, i.e., parametric and nonparametric, are fitted to the experimental data derived from static and dynamic tests to get the restoring force as a function of relative displacement and relative velocity across the joint. The resulting joint model exhibits a weakly nonlinear stiffness term and a viscous damping term. The results from both techniques are compared in the frequency domain. The advantages and disadvantages of parametric and nonparametric techniques are also discussed. The design of experiments for evaluating the nonlinearities in such industrial machine tool joints is a challenge, requiring careful alignment and calibration, because they are typically very stiff. This constrains the dynamic experiments to be carried out at high frequencies (e.g. 2000-7000Hz) where the experimental readings are very sensitive to errors in geometry and calibration.

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Drignei, Dorin, Zissimos P. Mourelatos, Vijitashwa Pandey, and Michael Kokkolaras. "Concurrent Design Optimization and Calibration-Based Validation Using Local Domains Sized by Bootstrapping." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-70423.

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The design optimization process relies often on computational models for analysis or simulation. These models must be validated to quantify the expected accuracy of the obtained design solutions. It can be argued that validation of computational models in the entire design space is neither affordable nor required. In previous work, motivated by the fact that most numerical optimization algorithms generate a sequence of candidate designs, we proposed a paradigm where design optimization and calibration-based model validation are performed concurrently in a sequence of variable-size local domains that are relatively small compared to the entire design space. A key element of this approach is how to account for variability in test data and model predictions in order to determine the size of the local domains at each stage of the sequential design optimization process. In this paper, we discuss two alternative techniques for accomplishing this: parametric and nonparametric bootstrapping. The parametric bootstrapping assumes a Gaussian distribution for the error between test and model data and uses maximum likelihood estimation to calibrate the prediction model. The nonparametric bootstrapping does not rely on the Gaussian assumption providing therefore, a more general way to size the local domains for applications where distributional assumptions are difficult to verify, or not met at all. If distribution assumptions are met, parametric methods are preferable over nonparametric methods. We use a validation literature benchmark problem to demonstrate the application of the two techniques, emphasizing that results cannot be compared. Which technique to use depends on whether the Gaussian distribution assumption is appropriate based on available information.

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Shubat, Oksana, and Mark Shubat. "Demographic And Statistical Modelling Of Grandfatherhood In Russia." In 35th ECMS International Conference on Modelling and Simulation. ECMS, 2021. http://dx.doi.org/10.7148/2021-0057.

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In recent years, negative demographic trends have been developing in Russia. The most important is a decline in the birth rate. Researchers are actively looking for new determinants of this process, on the basis of which measures of population policy can be developed. One of these determinants may be active grandparenting, which means the active participation of grandparents in the processes of caring for grandchildren. The aim of this study is to create a demographic and statistical model of a typical Russian grandfather, actively involved in childcare. We used the following methods: parametric and nonparametric independent samples tests (t-test, Mann-Whitney U test, median test), regression analysis, indirect method of calculations. As a result, two models were presented – statistical demographic model of the age when Russian men enter grandparenthood and demographic model of a typical Russian grandfather actively involved in childcare. Our study is a preliminary stage for a large-scale survey of grandparenting practices in Russia. The number of older people is growing fast, which makes this socio-economic group increasingly important for addressing the problems of demographic decline in Russia. Therefore, large-scale research of grandparenthood is crucial for more efficient policy-making in this sphere.

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Chati, Mandar, Curtis Johnson, Ahmet Kaya, and Bjoern Schenk. "Confidence Intervals for Weibull Fast-Fracture Parameters." In ASME Turbo Expo 2002: Power for Land, Sea, and Air. ASMEDC, 2002. http://dx.doi.org/10.1115/gt2002-30501.

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Practical limits on number of specimens that can be tested lead to uncertainty in the estimated Weibull parameters. This paper presents an evaluation of four techniques for estimating confidence intervals for size-scaled Weibull parameters of monolithic ceramics. The techniques include normal approximation method, likelihood ratio technique, nonparametric bootstrap, and parametric bootstrap methods. For uncensored fast-fracture data, the confidence intervals for Weibull parameters are compared to the method used in ASTM Standard C1239. A simulation fracture experiment is conducted to evaluate the statistical characteristics, in particular coverage probability, of the four methods. For fast-fracture data with multiple failure modes, the statistical assessment of the confidence interval techniques for size-scaled Weibull parameters complement the existing literature. Overall, it was observed that the likelihood ratio technique and parametric bootstrap method perform very well. These techniques can also be extended for confidence interval estimation using fast-fracture data obtained from various geometry’s of test specimens and/or loading conditions (pooled data).

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Hariyanti, Uun, and Wu-Yuin Hwang. "Design and Implementation of Ubiquitous Fraction App for Fraction Learning in Authentic Contexts." In International Conference on Education. The International Institute of Knowledge Management, 2020. http://dx.doi.org/10.17501/24246700.2020.6201.

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: An amount of research had identified some difficulties that were faced by students when they learned fractions, which is known as one of the essential parts of mathematics. On the other hand, designing mathematics learning in authentic contexts could beneficial to students, such as increase their motivation and collaboration. Thus, we develop a Ubiquitous App, namely Ubiquitous Fraction (U-Fraction), to facilitate fraction learning in authentic contexts by providing useful features. This study was designed to investigate the relationship among three categories of learning variables, including quantity of learning, quality of learning, and learning achievement, and to identify sequences of interactions when students use U-Fraction in authentic contexts. There were 27 five-grade students participated in this study. The data were analyzed using parametric and nonparametric tests, including pair t-test, correlation, lag sequential, and descriptive analysis. In summary, four important findings are highlighted in this study. First, the pair t-test result showed that there was a significant difference in students’ acquisition of fraction knowledge before and after the learning process. Second, the importance of correlation analysis results indicated that students’ learning achievement would depend more on their quality of learning rather than their quantity of tasks that had been solved by them. Third, results from sequential analysis indicated that students intended to do the next steps after they finished the previous step in fraction learning with authentic contexts. Fourth, a questionnaire, which is Sustainable and Scalable Authentic Learning (SSAL), results indicated that most students agree that learning with U-Fraction in authentic contexts could have a positive impact on the ability to collaborate with others. Finally, these results indicate that authentic learning supported by the Ubiquitous App can increase not only students’ achievements and engagements but also influence their positive attitude toward learning activities. Keywords: authentic contexts; ubiquitous fraction; authentic learning; peer sharing; peer assessment

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Duller, Christine, and Dominik Vorhauer. "Comparison of four nonparametric tests of symmetry." In INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2019. AIP Publishing, 2020. http://dx.doi.org/10.1063/5.0026685.

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Matteoli, Stefania, Marco Diani, and Giovanni Corsini. "Hybrid Parametric - Nonparametric Target Detector for Hyperspectral Images." In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. http://dx.doi.org/10.1109/igarss.2018.8519143.

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Lasocki, Stanislaw. "Parametric or nonparametric analysis of induced seismicity sequences." In Rock Mechanics in Petroleum Engineering. Society of Petroleum Engineers, 1994. http://dx.doi.org/10.2118/28107-ms.

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Ferrari-Trecate, G., and G. De Nicolao. "NARX models: optimal parametric approximation of nonparametric estimators." In Proceedings of American Control Conference. IEEE, 2001. http://dx.doi.org/10.1109/acc.2001.945754.

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Reports on the topic "Parametric and nonparametric tests"

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Andersen, Torben, Tim Bollerslev, and Francis Diebold. Parametric and Nonparametric Volatility Measurement. Cambridge, MA: National Bureau of Economic Research, August 2002. http://dx.doi.org/10.3386/t0279.

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Crump, Richard, V. Joseph Hotz, Guido Imbens, and Oscar Mitnik. Nonparametric Tests for Treatment Effect Heterogeneity. Cambridge, MA: National Bureau of Economic Research, June 2006. http://dx.doi.org/10.3386/t0324.

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Whang, Yoon-Jae, and Sokbae (Simon) Lee. Nonparametric tests of conditional treatment effects. Institute for Fiscal Studies, December 2009. http://dx.doi.org/10.1920/wp.cem.2009.3609.

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Haas, Timothy C., James T. Peterson, and Danny C. Lee. An Evaluation of Parametric and Nonparametric Models of Fish Population Response. Office of Scientific and Technical Information (OSTI), November 1999. http://dx.doi.org/10.2172/784173.

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Banzhaf, H. Spencer, Yaqin Liu, Martin Smith, and Frank Asche. Non-Parametric Tests of the Tragedy of the Commons. Cambridge, MA: National Bureau of Economic Research, October 2019. http://dx.doi.org/10.3386/w26398.

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Haile, Philip, Han Hong, and Matthew Shum. Nonparametric Tests for Common Values at First-Price Sealed-Bid Auctions. Cambridge, MA: National Bureau of Economic Research, November 2003. http://dx.doi.org/10.3386/w10105.

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Peterson, James T. CATDAT : A Program for Parametric and Nonparametric Categorical Data Analysis : User's Manual Version 1.0, 1998-1999 Progress Report. Office of Scientific and Technical Information (OSTI), December 1999. http://dx.doi.org/10.2172/756625.

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NUMERICAL STUDY ON SHEAR BEHAVIOUR OF ENHANCED C-CHANNELS IN STEEL-UHPC-STEEL SANDWICH STRUCTURES. The Hong Kong Institute of Steel Construction, September 2021. http://dx.doi.org/10.18057/ijasc.2021.17.3.4.

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This paper firstly developed a three-dimensional (3D) finite element model (FEM) for enhanced C-channels (ECs) in steel-UHPC-steel sandwich structures (SUSSSs). The FEM was validated by 12 push-out tests on ECs with UHPC. With the validated FEM, this paper performed in-depth parametric studies on shear behaviours of ECs with ultra-high performance concrete (UHPC). These investigated parameters included bolt-hole gap (a), grade (M) and diameter (d) of bolt, core strength (fc), length of C-channel (Lc), and prestressing force ratio on bolt (ρ) in ECs. Under shear forces, the ECs in UHPC exhibited successive fractures of bolts and C-channels. Increasing the bolt-hole gap within 0-2 mm has no harm on the ultimate shear resistance, but greatly improves the slip capacity of ECs. Increasing grade and diameter of bolts improves the shear resistance and ductility of ECs through increasing the PB/PC (shear strength of bolt to that of C-channel) ratio. Increasing the core strength increased the shear resistance, but reduced the ductility of ECs due to the reduced PB/PC ratio. The ECs with Lc value of 50 mm offer the best ductility. Prestressing force acting on the bolts reduced the shear strength and ductility of ECs with UHPC. Analytical models were proposed to estimate the ultimate shear resistance and shear-slip behaviours of ECs with UHPC. The extensive validations of these models against 12 tests and 31 FEM analysis cases proved their reasonable evaluations on shear behaviours of ECs with UHPC.

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