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Relevant bibliographies by topics / Asymmetrical factorial experiments

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Academic literature on the topic 'Asymmetrical factorial experiments'

Author: Grafiati

Published: 8 September 2023

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Journal articles on the topic "Asymmetrical factorial experiments"

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Gupta, V. K., Rajender Parsad, Lal Mohan Bhar, and Basudev Kole. "Supersaturated Designs for Asymmetrical Factorial Experiments." Journal of Statistical Theory and Practice 2, no. 1 (March 2008): 95–108. http://dx.doi.org/10.1080/15598608.2008.10411863.

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El-Helbawy, Abdalla T., Essam A. Ahmed, and Abdullah H. Alharbey. "Optimal designs for asymmetrical factorial paired comparison experiments." Communications in Statistics - Simulation and Computation 23, no. 3 (January 1994): 663–81. http://dx.doi.org/10.1080/03610919408813192.

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KUMAR, PRAKASH, KRISHAN LAL, ANIRBAN MUKHERJEE, UPENDRA KUMAR PRADHAN, MRINMOY RAY, and OM PRAKASH. "Advanced row-column designs for animal feed experiments." Indian Journal of Animal Sciences 88, no. 4 (January 5, 2023): 499–503. http://dx.doi.org/10.56093/ijans.v88i4.78895.

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Inappropriate statistical designs may misinterpret results of animal feed experiments. Thus complete statistical designs can make animal feed research more appropriate and cost effective. Usually factorial row-column designs are used when the heterogeneity in the experimental material is in two directions and the experimenter is interested in studying the effect of two or more factors simultaneously. Attempts have been to develop the method of construction of balanced nested row column design under factorial setup. Factorial experiments are used in designs when two or more factors have same levels or different levels. The designs that are balanced symmetric factorials nested in blocks are called block designs with nested row-column balanced symmetric factorial experiments. These designs were constructed by using confounding through equation methods.Construction of confounded asymmetrical factorial experiments in row-column settings and efficiency factor of confounded effects was worked out. The design can be used in animal feed experiment with fewer resources by not compromising the test accuracy.

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Agarwal, S. B., and M. N. Das. "Asymmetrical Factorial Type Switch over Designs." Calcutta Statistical Association Bulletin 35, no. 3-4 (September 1986): 149–56. http://dx.doi.org/10.1177/0008068319860304.

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In the present paper an attempt has been made to construct asymmetrical factorial type switch over designs having strip type arrangement of combination of the levels. To start with two factors at different levels have been considered. One factor has number of levels larger by one compared to the number of levels of other factor. The sequences of levels of second factor are associated with each level symbol of first factor. The situation is similar to strip plot designs in agricultural experiments. Method of construction along with analysis of these designs has been described in this paper.

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Divecha, Jyoti, and Bharat Tarapara. "Small, balanced, efficient, optimal, and near rotatable response surface designs for factorial experiments asymmetrical in some quantitative, qualitative factors." Quality Engineering 29, no. 2 (August 9, 2016): 196–210. http://dx.doi.org/10.1080/08982112.2016.1217338.

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Luis Pérez, Carmelo J. "On the Application of a Design of Experiments along with an ANFIS and a Desirability Function to Model Response Variables." Symmetry 13, no. 5 (May 18, 2021): 897. http://dx.doi.org/10.3390/sym13050897.

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In manufacturing engineering, it is common to use both symmetrical and asymmetrical factorial designs along with regression techniques to model technological response variables, since the in-advance prediction of their behavior is of great importance to determine the levels of variation that lead to optimal response values to be obtained. For this purpose, regression techniques based on the response surface method combined with a desirability function for multi-objective optimization are commonly employed, since it is usual to find manufacturing processes that require simultaneous optimization of several variables, which exhibit in many cases an opposite behavior. However, these regression models are sometimes not accurate enough to predict the behavior of these response variables, especially when they have significant non-linearities. To deal with this drawback, soft computing techniques are very effective in overcoming the limitations of conventional regression models. This present study is focused on the employment of a symmetrical design of experiments along with a new desirability function, which is proposed in this study, and with soft computing techniques based on fuzzy logic. It will be shown that more accurate results than those obtained from regression techniques are obtained. Moreover, this new desirability function is analyzed in this study.

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Voss, D. T. "On generalizations of the classical method of confounding to asymmetric factorial experiments." Communications in Statistics - Theory and Methods 15, no. 4 (January 1986): 1299–314. http://dx.doi.org/10.1080/03610928608829183.

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Das, Dipa Rani, and Sanjib Ghosh. "An Alternative Method of Construction and Analysis of Asymmetrical Factorial Experiment of the type 6x2² in Blocks of Size 12." Chittagong University Journal of Science 40, no. 1 (June 28, 2018): 137–50. http://dx.doi.org/10.3329/cujs.v40i1.47920.

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This paper focuses on the construction and analysis of an extra ordinary type of asymmetrical factorial experiment which corresponds to fraction of a symmetrical factorial experiment as indicated by Das (1960). For constructing this design, we have used 3 choices and for each choice we have used 5 different cases. Finding the block contents for each case we have seen that there are mainly two different cases for each choice. In case of analysis of variance, we have seen that, for the case where the highest order interaction effect is confounded in 4 replications, the loss of information is same for all the choices. Again for the case where the highest order interaction effect is confounded in 3 replications, the loss of information is also same for all the choices and one effect which is confounded due to fractionation has the same loss of information for all the choices. The Chittagong Univ. J. Sci. 40 : 137-150, 2018

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Chatterjee, K., P. Angelopoulos, and C. Koukouvinos. "A lower bound to the measure of optimality for main effect plans in the general asymmetric factorial experiments." Statistics 47, no. 2 (April 2013): 405–10. http://dx.doi.org/10.1080/02331888.2011.589905.

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Rubarth, Kerstin, Paavo Sattler, Hanna Gwendolyn Zimmermann, and Frank Konietschke. "Estimation and Testing of Wilcoxon–Mann–Whitney Effects in Factorial Clustered Data Designs." Symmetry 14, no. 2 (January 26, 2022): 244. http://dx.doi.org/10.3390/sym14020244.

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Clustered data arise frequently in many practical applications whenever units are repeatedly observed under a certain condition. One typical example for clustered data are animal experiments, where several animals share the same cage and should not be assumed to be completely independent. Standard methods for the analysis of such data are Linear Mixed Models and Generalized Estimating Equations—however, checking their assumptions is not easy, especially in scenarios with small sample sizes, highly skewed, count, and ordinal or binary data. In such situations, Wilcoxon–Mann–Whitney type effects are suitable alternatives to mean-based or other distributional approaches. Hence, no specific data distribution, symmetric or asymmetric, is required. Within this work, we will present different estimation techniques of such effects in clustered factorial designs and discuss quadratic- and multiple contrast type-testing procedures for hypotheses formulated in terms of Wilcoxon–Mann–Whitney effects. Additionally, the framework allows for the occurrence of missing data: estimation and testing hypotheses are based on all-available data instead of complete-cases. An extensive simulation study investigates the precision of the estimators and the behavior of the test procedures in terms of their type-I error control. One real world dataset exemplifies the applicability of the newly proposed procedures.

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Book chapters on the topic "Asymmetrical factorial experiments"

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"Confounding in Asymmetrical Factorial Designs." In Design and Analysis of Experiments, 466–506. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471709948.ch12.

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"Appendix D: Selected Asymmetrical Balanced Factorial Designs." In Design and Analysis of Experiments, 728–35. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471709948.app4.

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Conference papers on the topic "Asymmetrical factorial experiments"

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Han, L., M. Thornton, C. Chandrasekar, S. Maggs, and M. Shergold. "Effect of Specimen Dimensions on Mechanical Behavior of Resistant Spot Welded Aluminium Lap Joints." In ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2010. http://dx.doi.org/10.1115/esda2010-24289.

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A study was carried out to examine the effect of specimen dimensions on mechanical behavior of RSW welded joints. A full factorial Design of Experiment (DOE) approach was applied to the experimental process and analysis stages. Aluminium alloy AA5754 sheet in various thicknesses was used to form symmetrical and asymmetrical joints. Single lap shear test geometry with three dimensional changes; width, length and overlap at two-level, was tested throughout the project. The results demonstrated that for both symmetric and asymmetric stacks, the width of the specimen had a statistically significant effect on both failure mechanism and shear strength value of such joints; a strong interaction effect between length and overlap of the specimen on joint shear strength was observed. Although the strength variation is not substantial in engineering terms, the change in failure mechanism is significant and the results are useful in optimization of lap shear test standards and in comparison of joint strength obtained from different investigations with different specimen dimensions. It is also helpful in assisting structural and manufacturing engineers in design and development of RSW of aluminium for application.

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BAHR, Kadhim Mohammed, Meshal HARBI ODAH, and AliSadig Mohommed BAGER. "Application of Factorial Experiments with Asymmetric Responses for Determine Important Factors Affecting on Production of Dates." In 3rd Central & Eastern European LUMEN International Conference – New Approaches in Social and Humanistic Sciences | NASHS 2017| Chisinau, Republic of Moldova | June 8-10, 2017. LUMEN Publishing House, 2018. http://dx.doi.org/10.18662/lumproc.nashs2017.5.

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