Academic literature on the topic 'Logistic growth'
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Journal articles on the topic "Logistic growth"
Meyer, Perrin. "Bi-logistic growth." Technological Forecasting and Social Change 47, no. 1 (September 1994): 89–102. http://dx.doi.org/10.1016/0040-1625(94)90042-6.
Full textHieber, Matthias, Pablo Koch Medina, and Sandro Merino. "Diffusive logistic growth on." Nonlinear Analysis: Theory, Methods & Applications 27, no. 8 (October 1996): 879–94. http://dx.doi.org/10.1016/0362-546x(95)00035-t.
Full textTsoularis, A., and J. Wallace. "Analysis of logistic growth models." Mathematical Biosciences 179, no. 1 (July 2002): 21–55. http://dx.doi.org/10.1016/s0025-5564(02)00096-2.
Full textKucharavy, Dmitry, and Roland De Guio. "Application of Logistic Growth Curve." Procedia Engineering 131 (2015): 280–90. http://dx.doi.org/10.1016/j.proeng.2015.12.390.
Full textGopalsamy, K., and Pei-Xuan Weng. "Feedback regulation of logistic growth." International Journal of Mathematics and Mathematical Sciences 16, no. 1 (1993): 177–92. http://dx.doi.org/10.1155/s0161171293000213.
Full textShah, Md Asaduzzaman. "Stochastic Logistic Model for Fish Growth." Open Journal of Statistics 04, no. 01 (2014): 11–18. http://dx.doi.org/10.4236/ojs.2014.41002.
Full textAwadalla, Muath, Yves Yannick Yameni Noupoue, and Kinda Abu Asbeh. "Psi-Caputo Logistic Population Growth Model." Journal of Mathematics 2021 (July 26, 2021): 1–9. http://dx.doi.org/10.1155/2021/8634280.
Full textAntonelli, Peter L. "Filtering then-dimensional logistic growth model." Stochastic Analysis and Applications 8, no. 3 (January 1990): 263–92. http://dx.doi.org/10.1080/07362999008809209.
Full textWebb, G. F. "Logistic models of structured population growth." Computers & Mathematics with Applications 12, no. 4-5 (April 1986): 527–39. http://dx.doi.org/10.1016/0898-1221(86)90178-1.
Full textTUCKWELL, H., and J. KOZIOL. "Logistic population growth under random dispersal." Bulletin of Mathematical Biology 49, no. 4 (1987): 495–506. http://dx.doi.org/10.1016/s0092-8240(87)80010-1.
Full textDissertations / Theses on the topic "Logistic growth"
Molla, Mohammad Mofigul Islam. "A Stochastic Bayesian Update and Logistic Growth Mapping of Travel-Time Flow Relationship." Diss., North Dakota State University, 2017. http://hdl.handle.net/10365/25911.
Full textIrvine, Paul Michael. "Using a logistic phenology model with improved degree-day accumulators to forecast emergence of pest grasshoppers." Thesis, Lethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer Science, 2011, 2011. http://hdl.handle.net/10133/3105.
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Fay, TH, and JC Greeff. "A three species competition model as a decision support tool." Elsevier, 2007. http://encore.tut.ac.za/iii/cpro/DigitalItemViewPage.external?sp=1000167.
Full textFossceco, Stewart Lee. "Logistic growth curve parameter estimates for scrotal circumference and relationships with female reproduction in crossbred sheep." Diss., Virginia Tech, 1991. http://hdl.handle.net/10919/37241.
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Browning, Alexander P. "Stochastic mathematical models of cell proliferation assays." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/110808/1/Alexander_Browning_Thesis.pdf.
Full textJohnson, Vicki D. "Growth Mindset as a Predictor of Smoking Cessation." Cleveland State University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=csu1246034970.
Full textWasson, Samantha Rae. "Increasing Introductory Biology Students' Modeling Mastery Through Visualizing Population Growth Models." BYU ScholarsArchive, 2021. https://scholarsarchive.byu.edu/etd/9181.
Full textMurphy, Stephen J. "Vegetation Dynamics of an Old-growth Mixed Mesophytic Forest in Southeastern Ohio, USA." Ohio University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1350941088.
Full textBara, Carlos Roberto Francisco. "Variáveis relevantes para as empresas de alto crescimento no Brasil." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/12/12139/tde-11062018-114840/.
Full textEntrepreneurship has been object of encouragement in the world and in Brazil, given its significant contribution to the economic and social development of a nation. It is observed that the majority of companies, existing or new, are developing slowly and gradually; however, small share presents a different pattern, with high growth in sales or number of employees: they are the high growth firms (HGFs). These firms are responsible for a large part of job creation (Birch, 1981; Coad, Daunfeldt, Holzl, Johansson, & Nightingale, 2014, Henrekson & Johansson, 2010, OECD, 2010). This thesis aimed to identify the variables that help to explain the performance of HGFs in Brazil, according to OECD (2007) criterion. A survey with 470 Brazilian companies was conducted, collecting more than 30 categorical or metric predictor variables, used in the Logistic Regression model. Some identified variables were aligned to literature, but others less intuitive or documented. It was confirmed the increase in the probability of HGFs when they related to accelerators, received awards, or were spin-offs of other companies. As a consequence of the high banking interest rates and the entrepreneurship culture in Brazil, surprised the positive impact of bank loans and the entrepreneurs\' perception of trademark registration, as well as the negative impact of perception on advertising in digital media and donations from development institutions, related to HGFs. Additional analyzes with the subgroup of HGFs characterized as gazelles were made. Although it presents limitations of surveys and others, the thesis confirmed part of the results of the literature on entrepreneurship and identified avenues for future researches.
Atems, Bebonchu. "Essays in nonlinear macroeconomic modeling and econometrics." Diss., Kansas State University, 2011. http://hdl.handle.net/2097/11985.
Full textDepartment of Economics
Lance J. Bachmeier
This dissertation consists of three essays in nonlinear macroeconomic modeling and econometrics. In the first essay, we decompose oil price movements into oil demand (stock market) shocks and oil supply (oil-market) shocks, and examine the response of the stock market to these shocks. We find that when oil prices are “net-increasing”, a stock market shock that causes the S&P 500 to rise by one percentage point will cause the price of oil to rise approximately 0.2 percentage points, with a statistically significant positive effect one day after the stock market shock. On the other hand, the response of the stock market to an oil market shock is a decline of 6.8 percent when the price of oil doubles. For other days, the initial response of the oil market to a stock market shock is the same as in the net oil price increase case (by construction). We then analyze the response of monetary policy to the identified stock market and oil market shocks and find that short-term interest rates respond to the stock market shocks but not the oil market shocks. Finally, we evaluate the predictive power of the decomposed stock market and oil shocks relative to the change in the price of oil. We find statistically significant gains in both the in-sample fit and out-of-sample forecast accuracy when using the identified stock market and oil market shocks rather than the change in the price of oil. The second essay revisits the statistical specification of near-multicollinearity in the logistic regression model using the Probabilistic Reduction approach. We argue that the ceteris paribus clause invoked with near-multicollinearity is rather misleading. This assumption states that one can assess the impact of near-multicollinearity by holding the parameters of the logistic regression model constant, while examining the impact on their standard errors and t-ratios as the correlation (\rho) between the regressors increases. Using the Probabilistic Reduction approach, we derive the parameters (and related statisitics) of the logistic regression model and show that they are functions of \rho , indicating the ceteris paribus clause in the traditional account of near multicollinearity is unattainable. Monte carlo simulations in the paper confirm these findings. We also show that traditional near-multicollinearity diagnostics, such as the variance inflation factor and condition number can fail to detect near-multicollinearity. Overall, the paper finds that near-multicollinearity in the logistic model is highly variable and may not lead to the problems indicated by the traditional account. Therefore, unexpected, unreliable or unstable estimates and inferences should not be blamed on near-multicollinearity. Rather the modeler should return to economic theory or statistical respecification of their model to address these problems. The third essay examines the correlations between income inequality and economic growth using a panel of income distribution data for 3,109 counties of the U.S. We examine the non-spatial dynamic correlations between county inequality and growth using a System GMM approach, and find significant negative relationships between changes in inequality in one period and growth in the subsequent period. We show that this finding is robust across different sample sizes. We further argue that because the space-specific time-invariant variables that affect economic growth and inequality can differ significantly across counties, failure to incorporate spatial effects into a model of growth and inequality may lead to biased results.We assume that dependence among counties only arises from the disturbance process, hence the estimation of a spatial error model. Our results indicate that the bias in the parameter for inequality amounts to about 2.66 percent, while that for initial income amounts to about 21.51 percent.
Books on the topic "Logistic growth"
Gaver, Donald Paul. Note on an alternative mechanism for logistic growth. Monterey, Calif: Naval Postgraduate School, 1995.
Find full textLogistics clusters: Delivering value and driving growth. Cambridge, Mass: MIT Press, 2012.
Find full textCreating entrepreneurial supply chains: A guide for innovation and growth. Ft. Lauderdale, FL: J. Ross Pub., 2012.
Find full textLingling, Peng, ed. Zhujiang Sanjiaozhou gang kou wu liu yu cheng shi fa zhan. Beijing: Shang wu yin shu guan, 2011.
Find full textHofmann, Erik. Ways out of the working capital trap: Empowering self-financing growth through modern supply management. Heidelberg: Springer, 2011.
Find full textUddin, Aman. The application of logistics process re-engineering to improve distribution network of furniture retailer Heal's and sustain its furniture business growth. London: LCP, 2002.
Find full textOffice, General Accounting. Defense inventory: Growth in secondary items : briefing report to Congressional requesters. Washington, D.C: The Office, 1988.
Find full textOffice, General Accounting. Defense inventory: Growth in secondary items : briefing report to Congressional requesters. Washington, D.C: The Office, 1988.
Find full textFerber, Martin M. Department of Defense inventory growth and management problems continue: Statement for the record of Martin M. Ferber, Senior Associate Director, before the Subcommittee on Readiness Committee on Armed Services United States House of Representatives. [Washington, D.C.?]: United States General Accounting Office, 1988.
Find full textOffice, General Accounting. Depot maintenance: Public-private partnerships have increased, but long-term growth and results are uncertain : report to the Subcommittee on Readiness, Committee on Armed Services, House of Representatives. Washington, D.C. (P.O. Box 37050, Washington, D.C. 20013): U.S. General Accounting Office, 2003.
Find full textBook chapters on the topic "Logistic growth"
Miller, Laura T., Lionel Stange, Charles MacVean, Jorge R. Rey, J. H. Frank, R. F. Mizell, John B. Heppner, et al. "Logistic Growth." In Encyclopedia of Entomology, 2225. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6359-6_2073.
Full textLopez, Robert J. "Logistic Growth." In Maple via Calculus, 85–87. Boston, MA: Birkhäuser Boston, 1994. http://dx.doi.org/10.1007/978-1-4612-0267-7_22.
Full textSwishchuk, Anatoly, and Jianhong Wu. "Logistic Growth Models." In Evolution of Biological Systems in Random Media: Limit Theorems and Stability, 175–85. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-1506-5_7.
Full textLanchier, Nicolas. "Logistic growth process." In Stochastic Modeling, 193–201. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-50038-6_11.
Full textDavid, H. A., and A. W. F. Edwards. "The Logistic Growth Curve." In Springer Series in Statistics, 65–67. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4757-3500-0_11.
Full textSchwalbe, Dan, and Stan Wagon. "Logistic Models of Population Growth." In VisualDSolve, 145–52. New York, NY: Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4612-2250-7_9.
Full textConrado, Claudine V., and Tomas Bohr. "Ordering Process in the Diffusively Coupled Logistic Lattice." In Growth and Form, 457–64. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4684-1357-1_41.
Full textShearer, S. F. C., S. Sahoo, and A. Sahoo. "Stochastic Dynamics of Logistic Tumor Growth." In Stochastic Algorithms: Foundations and Applications, 206–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04944-6_17.
Full textArmstrong, Richard A., and Anthony C. Hilton. "Nonlinear Regression: Fitting A Logistic Growth Curve." In Statistical Analysis in Microbiology: Statnotes, 119–22. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9780470905173.ch23.
Full textZine, Houssine, Jaouad Danane, and Delfim F. M. Torres. "A Stochastic Capital-Labour Model with Logistic Growth Function." In Dynamic Control and Optimization, 231–41. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17558-9_13.
Full textConference papers on the topic "Logistic growth"
Clark, Aaron James, Larry Wayne Lake, and Tadeusz Wiktor Patzek. "Production Forecasting with Logistic Growth Models." In SPE Annual Technical Conference and Exhibition. Society of Petroleum Engineers, 2011. http://dx.doi.org/10.2118/144790-ms.
Full textTao, Jin, and Gao Deyong. "Study of logistic growth curve model for mobile user growth." In 2012 3rd International Conference on System Science, Engineering Design and Manufacturing Informatization (ICSEM). IEEE, 2012. http://dx.doi.org/10.1109/icssem.2012.6340840.
Full textWindarto, Eridani, and Utami Dyah Purwati. "Implementation of Fractional Logistic Growth Model in Describing Rooster Growth." In 2nd International Conference Postgraduate School. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0007547505830586.
Full textMačiulytė-Šniukienė, Alma, and Aurelija Burinskienė. "Logistics and international trade development relationship: evidence of European Union member states." In 11th International Scientific Conference „Business and Management 2020“. VGTU Technika, 2020. http://dx.doi.org/10.3846/bm.2020.524.
Full text"A Cell-DEVS Model for Logistic Urban Growth." In 2019 Spring Simulation Conference. Society for Modeling and Simulation International (SCS), 2019. http://dx.doi.org/10.22360/springsim.2019.anss.019.
Full textSt-Aubin, Bruno, and Gabriel Wainer. "A Cell-Devs Model for Logistic Urban Growth." In 2019 Spring Simulation Conference (SpringSim). IEEE, 2019. http://dx.doi.org/10.23919/springsim.2019.8732910.
Full textMoroza, Nadina, and Inguna Jurgelane-Kaldava. "Theoretical analysis of factors affecting the development of logistics centre." In 21st International Scientific Conference "Economic Science for Rural Development 2020". Latvia University of Life Sciences and Technologies. Faculty of Economics and Social Development, 2020. http://dx.doi.org/10.22616/esrd.2020.53.024.
Full textLa Torre, Davide, Danilo Liuzzi, and Simone Marsiglio. "A Note on Stochastic Logistic Shocks and Economic Growth." In 2019 8th International Conference on Modeling Simulation and Applied Optimization (ICMSAO). IEEE, 2019. http://dx.doi.org/10.1109/icmsao.2019.8880319.
Full textLuo, Jun, and Nagaraj Kapi Kanala. "Modeling urban growth with geographically weighted multinomial logistic regression." In Geoinformatics 2008 and Joint conference on GIS and Built Environment: The Built Environment and its Dynamics, edited by Lin Liu, Xia Li, Kai Liu, Xinchang Zhang, and Xinhao Wang. SPIE, 2008. http://dx.doi.org/10.1117/12.812714.
Full textJain, Preeti N., and Sunil K. Surve. "Modeling resource constrained solo applications using logistic growth model." In 2017 International Conference on Advances in Computing, Communication and Control (ICAC3). IEEE, 2017. http://dx.doi.org/10.1109/icac3.2017.8318751.
Full textReports on the topic "Logistic growth"
Gaver, Donald P., Patricia A. Jacobs, and Robert L. Carpenter. Note on An Alternative Mechanism for Logistic Growth. Fort Belvoir, VA: Defense Technical Information Center, November 1995. http://dx.doi.org/10.21236/ada302175.
Full textIyer, Ananth V., Thomas Brady, Steven R. Dunlop, Dutt J. Thakkar, Saichandar Naini, Srinath Jayan, Suraj Vasu, Sanjayraj Mohanraj, and Janani Srinvasan. Forecasting Freight Logistic Needs and INDOT Plans. Purdue University, 2022. http://dx.doi.org/10.5703/1288284317372.
Full textJagannathan, Shanti, and Dorothy Geronimo. Reaping the Benefits of Industry 4.0 through Skills Development in Viet Nam. Asian Development Bank, January 2021. http://dx.doi.org/10.22617/spr200308.
Full textMcGregor, Lisa, Sarah Frazer, and Derick Brinkerhoff. Thinking and Working Politically: Lessons from Diverse and Inclusive Applied Political Economy Analysis. RTI Press, April 2020. http://dx.doi.org/10.3768/rtipress.2020.rr.0038.2004.
Full textTaucher, Jan, and Markus Schartau. Report on parameterizing seasonal response patterns in primary- and net community production to ocean alkalinization. OceanNETs, November 2021. http://dx.doi.org/10.3289/oceannets_d5.2.
Full textKyrgyz Republic: Improving Growth Potential: Country Diagnostic Study in Russian. Asian Development Bank, October 2020. http://dx.doi.org/10.22617/tcs190441-2.
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