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Journal articles on the topic 'Functional model'

Author: Grafiati
Published: 4 June 2021
Last updated: 5 May 2022

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1

Horák, Karel, and Vladimír Müller. "Functional model for commuting isometries." Czechoslovak Mathematical Journal 39, no. 2 (1989): 370–79. http://dx.doi.org/10.21136/cmj.1989.102308.

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2

Lei, Y., and S. Y Zhang. "Comparison and selection of growth models using the Schnute model." Journal of Forest Science 52, No. 4 (January 9, 2012): 188–96. http://dx.doi.org/10.17221/4501-jfs.

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Forestmodellers have long faced the problem of selecting an appropriate mathematical model to describe tree ontogenetic or size-shape empirical relationships for tree species. A common practice is to develop many models (or a model pool) that include different functional forms, and then to select the most appropriate one for a given data set. However, this process may impose subjective restrictions on the functional form. In this process, little attention is paid to the features (e.g. asymptote and inflection point rather than asymptote and nonasymptote) of different functional forms, and to the intrinsic curve of a given data set. In order to find a better way of comparing and selecting the growth models, this paper describes and analyses the characteristics of the Schnute model. This model has both flexibility and versatility that have not been used in forestry. In this study, the Schnute model was applied to different data sets of selected forest species to determine their functional forms. The results indicate that the model shows some desirable properties for the examined data sets, and allows for discerning the different intrinsic curve shapes such as sigmoid, concave and other curve shapes. Since no suitable functional form for a given data set is usually known prior to the comparison of candidate models, it is recommended that the Schnute model be used as the first step to determine an appropriate functional form of the data set under investigation in order to avoid using a functional form a priori.
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3

Tryhuk, Václav. "Functional equations and a theoretical model of DLTS." Applications of Mathematics 40, no. 6 (1995): 473–82. http://dx.doi.org/10.21136/am.1995.134308.

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4

Cardot, Hervé, Frédéric Ferraty, and Pascal Sarda. "Functional linear model." Statistics & Probability Letters 45, no. 1 (October 1999): 11–22. http://dx.doi.org/10.1016/s0167-7152(99)00036-x.

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5

Bücher, Axel, Holger Dette, and Gabriele Wieczorek. "Testing model assumptions in functional regression models." Journal of Multivariate Analysis 102, no. 10 (November 2011): 1472–88. http://dx.doi.org/10.1016/j.jmva.2011.05.014.

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6

Elida, Fuster Guillén Doris. "New functional model of research skills in social problem solving." International Journal of Early Childhood Special Education 12, no. 1 (June 30, 2020): 442–51. http://dx.doi.org/10.9756/int-jecse/v12i1.201024.

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7

Kennedy, John, Stephen M. Matyas, and Nevenko Zunic. "Key Recovery Functional Model." Computers & Security 19, no. 1 (January 2000): 31–36. http://dx.doi.org/10.1016/s0167-4048(00)86360-9.

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8

Quinn, James H. "A functional TMJ model." Journal of the American Dental Association 120, no. 3 (March 1990): 234. http://dx.doi.org/10.14219/jada.archive.1990.0062.

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9

Lian, Heng. "Functional partial linear model." Journal of Nonparametric Statistics 23, no. 1 (March 2011): 115–28. http://dx.doi.org/10.1080/10485252.2010.500385.

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10

James, Gareth M., and Bernard W. Silverman. "Functional Adaptive Model Estimation." Journal of the American Statistical Association 100, no. 470 (June 2005): 565–76. http://dx.doi.org/10.1198/016214504000001556.

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11

Zouagui, T., H. Benoit-Cattin, and C. Odet. "Image segmentation functional model." Pattern Recognition 37, no. 9 (September 2004): 1785–95. http://dx.doi.org/10.1016/j.patcog.2003.12.014.

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12

Orman, Levent. "Functional data model design." Information Systems 11, no. 2 (January 1986): 123–35. http://dx.doi.org/10.1016/0306-4379(86)90002-5.

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13

Lee, Kuang‐Yao, and Lexin Li. "Functional structural equation model." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 84, no. 2 (March 21, 2022): 600–629. http://dx.doi.org/10.1111/rssb.12471.

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14

HIRAMATSU, Shigeki, Shizuo SUMIDA, and Akio NAGAMATSU. "Hierarchical Functional Model for Automobile Development. 3rd Report. Functional Model of Drivetrain." Transactions of the Japan Society of Mechanical Engineers Series C 68, no. 671 (2002): 2090–97. http://dx.doi.org/10.1299/kikaic.68.2090.

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15

Tucci, Beatriz Ferreira Martins, and Magda Lúcia Félix de Oliveira. "Alcoholic beverage users: structural and functional aspects based on the Calgary Model." Revista da Rede de Enfermagem do Nordeste 20 (April 3, 2019): e40226. http://dx.doi.org/10.15253/2175-6783.20192040226.

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16

Kawamura, Shinsuke, Ken'ichi Koyanagi, Tatsuo Motoyoshi, Hiroyuki Masuta, and Toru Oshima. "Functional Verification with a Scale Model for Movable Type Power Assist System." Abstracts of the international conference on advanced mechatronics : toward evolutionary fusion of IT and mechatronics : ICAM 2015.6 (2015): 165–66. http://dx.doi.org/10.1299/jsmeicam.2015.6.165.

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17

Zhu, Hongxiao, Philip J. Brown, and Jeffrey S. Morris. "Robust, Adaptive Functional Regression in Functional Mixed Model Framework." Journal of the American Statistical Association 106, no. 495 (September 2011): 1167–79. http://dx.doi.org/10.1198/jasa.2011.tm10370.

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18

Wang, Guochang, Baoxue Zhang, Wenhui Liao, and Baojian Xie. "Estimation of functional regression model via functional dimension reduction." Journal of Computational and Applied Mathematics 379 (December 2020): 112948. http://dx.doi.org/10.1016/j.cam.2020.112948.

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19

Саранчук, Юрий, Yuriy Saranchuk, Игорь Мукиенко, and Igor Mukienko. "FUNCTIONAL MODEL OF ADMINISTRATIVE LAW." Advances in Law Studies 6, no. 2 (September 20, 2018): 20–25. http://dx.doi.org/10.29039/article_5b85b382a67ef7.08311690.

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The article considers a methodological approach to the analysis of administrative law as a system. The basis of this approach is the different content characteristic of the category "function" in the theory of administrative law. A brief overview of legal models based on the regulatory and protective functions of administrative law, public administration functions, and the functions of federal executive bodies is given.
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20

Kim, Janet S., Arnab Maity, and Ana-Maria Staicu. "Additive nonlinear functional concurrent model." Statistics and Its Interface 11, no. 4 (2018): 669–85. http://dx.doi.org/10.4310/sii.2018.v11.n4.a11.

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21

Doronina, Inna, and Svetlana Londar. "Designing municipal library functional model." Scientific and Technical Libraries, no. 4 (April 1, 2016): 5–15. http://dx.doi.org/10.33186/1027-3689-2016-4-5-15.

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The conclusions on using functional modeling results for library processes modernization are presented. The authors prove that such functional models make the basis for efficient information services. The study was accomplished at Valuy district Intersettlement Library, Belgorod Oblast, Russia.
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22

Malfait, Nicole, and James O. Ramsay. "The historical functional linear model." Canadian Journal of Statistics 31, no. 2 (June 2003): 115–28. http://dx.doi.org/10.2307/3316063.

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23

Chaplinska, Iuliia. "FUNCTIONAL MODEL OF PARASOCIAL RELATIONS." Psychological journal 6, no. 5 (May 28, 2020): 66–79. http://dx.doi.org/10.31108/1.2020.6.5.6.

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24

Vasconcellos, Muriel. "A Functional Model of Translation." Babel. Revue internationale de la traduction / International Journal of Translation 32, no. 3 (January 1, 1986): 134–45. http://dx.doi.org/10.1075/babel.32.3.03vas.

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25

Kulkarni, K. G. "EFDM: Extended Functional Data Model." Computer Journal 29, no. 1 (January 1, 1986): 38–46. http://dx.doi.org/10.1093/comjnl/29.1.38.

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26

Hossein Keshavarz, Mohammad. "Halliday's Communicative-Functional Model Revisited." Communication Disorders Quarterly 22, no. 4 (September 2001): 187–96. http://dx.doi.org/10.1177/152574010102200404.

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27

Blackburne, Benjamin P., and Jonathan D. Hirst. "Evolution of functional model proteins." Journal of Chemical Physics 115, no. 4 (July 22, 2001): 1935–42. http://dx.doi.org/10.1063/1.1383051.

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28

Chun, Alexa L., Lane J. Wallace, Michael C. Gerald, Alan J. Wein, and Robert M. Levin. "Functional whole rat bladder model." Neurourology and Urodynamics 8, no. 1 (1989): 73–83. http://dx.doi.org/10.1002/nau.1930080108.

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29

Halevy, Nir, Eileen Y. Chou, and Adam D. Galinsky. "A functional model of hierarchy." Organizational Psychology Review 1, no. 1 (February 2011): 32–52. http://dx.doi.org/10.1177/2041386610380991.

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30

Daugherty, Patricia J., Dale S. Rogers, and Michael S. Spencer. "Just‐in‐time Functional Model." International Journal of Physical Distribution & Logistics Management 24, no. 6 (August 1994): 20–26. http://dx.doi.org/10.1108/09600039410066150.

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31

Brockhaus, Sarah, Fabian Scheipl, Torsten Hothorn, and Sonja Greven. "The functional linear array model." Statistical Modelling: An International Journal 15, no. 3 (January 14, 2015): 279–300. http://dx.doi.org/10.1177/1471082x14566913.

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32

Teipel, S., and B. Krebs. "A functional model for monooxygenases." Journal of Inorganic Biochemistry 47, no. 3-4 (July 1992): 60. http://dx.doi.org/10.1016/0162-0134(92)84158-j.

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33

Escabias, M., A. M. Aguilera, and M. J. Valderrama. "Functional PLS logit regression model." Computational Statistics & Data Analysis 51, no. 10 (June 2007): 4891–902. http://dx.doi.org/10.1016/j.csda.2006.08.011.

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34

Soares, Rafael de P., and Renan P. Gerber. "Functional-Segment Activity Coefficient Model. 1. Model Formulation." Industrial & Engineering Chemistry Research 52, no. 32 (April 17, 2013): 11159–71. http://dx.doi.org/10.1021/ie400170a.

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35

HIRAMATSU, Shigeki, Shizuo SUMIDA, Akio NAGAMATSU, and Hiroyuki ARAKAWA. "Hierarchical Functional Model for Automobile Development. 2nd Report. Functional and Mechanical Models of Engine." Transactions of the Japan Society of Mechanical Engineers Series C 68, no. 671 (2002): 2082–89. http://dx.doi.org/10.1299/kikaic.68.2082.

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36

Lunel, Sjoerd M. Verduyn, and Dmitry V. Yakubovich. "A functional model approach to linear neutral functional differential equations." Integral Equations and Operator Theory 27, no. 3 (September 1997): 347–78. http://dx.doi.org/10.1007/bf01324734.

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37

Zhang, Haili, and Guohua Zou. "Cross-Validation Model Averaging for Generalized Functional Linear Model." Econometrics 8, no. 1 (February 24, 2020): 7. http://dx.doi.org/10.3390/econometrics8010007.

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Functional data is a common and important type in econometrics and has been easier and easier to collect in the big data era. To improve estimation accuracy and reduce forecast risks with functional data, in this paper, we propose a novel cross-validation model averaging method for generalized functional linear model where the scalar response variable is related to a random function predictor by a link function. We establish asymptotic theoretical result on the optimality of the weights selected by our method when the true model is not in the candidate model set. Our simulations show that the proposed method often performs better than the commonly used model selection and averaging methods. We also apply the proposed method to Beijing second-hand house price data.
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38

Naiman, Joseph, and Peter Xuekun Song. "Multivariate Functional Kernel Machine Regression and Sparse Functional Feature Selection." Entropy 24, no. 2 (January 28, 2022): 203. http://dx.doi.org/10.3390/e24020203.

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Motivated by mobile devices that record data at a high frequency, we propose a new methodological framework for analyzing a semi-parametric regression model that allow us to study a nonlinear relationship between a scalar response and multiple functional predictors in the presence of scalar covariates. Utilizing functional principal component analysis (FPCA) and the least-squares kernel machine method (LSKM), we are able to substantially extend the framework of semi-parametric regression models of scalar responses on scalar predictors by allowing multiple functional predictors to enter the nonlinear model. Regularization is established for feature selection in the setting of reproducing kernel Hilbert spaces. Our method performs simultaneously model fitting and variable selection on functional features. For the implementation, we propose an effective algorithm to solve related optimization problems in that iterations take place between both linear mixed-effects models and a variable selection method (e.g., sparse group lasso). We show algorithmic convergence results and theoretical guarantees for the proposed methodology. We illustrate its performance through simulation experiments and an analysis of accelerometer data.
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39

Горленко, Олег, Oleg Gorlenko, Татьяна Можаева, Tatyana Mozhaeva, Александр Проскурин, and Aleksandr Proskurin. "FUNCTIONAL MODEL OF EDUCATIONAL INSTITUTION MANAGEMENT." Bulletin of Bryansk state technical university 2018, no. 12 (December 18, 2018): 87–92. http://dx.doi.org/10.30987/article_5c0f8097ecd513.19409794.

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40

Kozhedub, Yuliia. "Functional model of information security systems." Collection "Information technology and security" 6, no. 2 (December 30, 2018): 29–42. http://dx.doi.org/10.20535/2411-1031.2018.6.2.153488.

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41

Zhylin, Artem, Mykola Hudyncev, and Maksym Litvinov. "Functional model of cybersecurity situation center." Collection "Information technology and security" 6, no. 2 (December 30, 2018): 51–67. http://dx.doi.org/10.20535/2411-1031.2018.6.2.153490.

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42

Strachkova, N. V., and A. Yu Popova. "WINE CLUSTER MODEL: STRUCTURAL-FUNCTIONAL ASPECT." Географический вестник = Geographical bulletin, no. 4(43) (2017): 169–75. http://dx.doi.org/10.17072/2079-7877-2017-4-169-175.

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43

Danigo, Aurore, Laurent Magy, Laurence Richard, Franck Sturtz, Benoît Funalot, and Claire Demiot. "A reversible functional sensory neuropathy model." Neuroscience Letters 571 (June 2014): 39–44. http://dx.doi.org/10.1016/j.neulet.2014.04.026.

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44

Wong, Heung, Riquan Zhang, Wai-cheung Ip, and Guoying Li. "Functional-coefficient partially linear regression model." Journal of Multivariate Analysis 99, no. 2 (February 2008): 278–305. http://dx.doi.org/10.1016/j.jmva.2007.03.003.

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45

Sumida, S. "Hierarchical functional model for automobile development." JSAE Review 19, no. 4 (October 1, 1998): 368–71. http://dx.doi.org/10.1016/s0389-4304(98)00032-0.

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46

Tsurugizawa, Tomokazu. "Pharmacological Functional MRI in Rodent Model." Current Psychopharmacology 6, no. 1 (April 5, 2017): 4–11. http://dx.doi.org/10.2174/2211556005666160901150718.

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47

Fiksenbaum, Lisa M., Esther R. Greenglass, Sandra R. Marques, and Judy Eaton. "A psychosocial model of functional disability." Ageing International 30, no. 3 (September 2005): 278–95. http://dx.doi.org/10.1007/s12126-005-1016-9.

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48

Davidson, Stephen F., Shelby K. Brantley, Paul J. Talbot, and Suman K. Das. "A Functional Model of Microvascular Thrombosis." Plastic and Reconstructive Surgery 86, no. 3 (September 1990): 579–81. http://dx.doi.org/10.1097/00006534-199009000-00036.

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49

Brown, Fredda, Ian M. Evans, Keri A. Weed, and Valerie Owen. "Delineating Functional Competencies: A Component Model." Journal of the Association for Persons with Severe Handicaps 12, no. 2 (June 1987): 117–24. http://dx.doi.org/10.1177/154079698701200205.

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This article describes a model for representing functional competencies in students with disabilities. Although strategies exist to identify skills and activities that are functional for students with severe handicaps, these strategies provide relatively little information on how to separate the functional skills into meaningful component parts that represent the range of behaviors needed in the natural environment. Data are presented to illustrate the narrow range of behaviors included in task analyses in current literature on skill acquisition. The Component Model of Functional Life Routines provides a systematic alternate approach to delineating the behaviors required in natural environments.
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50

Jones, Andrew R., Angel Pizarro, Paul Spellman, and Michael Miller. "FuGE: Functional Genomics Experiment Object Model." OMICS: A Journal of Integrative Biology 10, no. 2 (June 2006): 179–84. http://dx.doi.org/10.1089/omi.2006.10.179.

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