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Статті в журналах з теми "Probability mass functions"
Gilbert, L., G. de Cooman, and E. E. Kerre. "Practical implementation of possibilistic probability mass functions." Soft Computing - A Fusion of Foundations, Methodologies and Applications 7, no. 5 (April 1, 2003): 304–9. http://dx.doi.org/10.1007/s00500-002-0217-3.
Повний текст джерелаRacine, Jeffrey S., Qi Li, and Karen X. Yan. "Kernel smoothed probability mass functions for ordered datatypes." Journal of Nonparametric Statistics 32, no. 3 (May 12, 2020): 563–86. http://dx.doi.org/10.1080/10485252.2020.1759595.
Повний текст джерелаDrane, J. Wanzer, Suhua Cao, Lixia Wang, and T. Postelnicu. "Limiting Forms of Probability Mass Functions via Recurrence Formulas." American Statistician 47, no. 4 (November 1993): 269. http://dx.doi.org/10.2307/2685285.
Повний текст джерелаDrane, J. Wanzer, Suhua Cao, Lixia Wang, and T. Postelnicu. "Limiting forms of Probability Mass Functions via Recurrence Formulas." American Statistician 47, no. 4 (November 1993): 269–74. http://dx.doi.org/10.1080/00031305.1993.10475996.
Повний текст джерелаBergbusch, Peter A. "Isochrone Probability Functions for Old Stellar Systems." Symposium - International Astronomical Union 190 (1999): 345–46. http://dx.doi.org/10.1017/s0074180900118170.
Повний текст джерелаProvost, Serge B., Min Jiang, and Hyung-Tae Ha. "Moment-Based Approximations of Probability Mass Functions with Applications Involving Order Statistics." Communications in Statistics - Theory and Methods 38, no. 12 (June 3, 2009): 1969–81. http://dx.doi.org/10.1080/03610920902835052.
Повний текст джерелаWarr, Richard L. "Numerical Approximation of Probability Mass Functions via the Inverse Discrete Fourier Transform." Methodology and Computing in Applied Probability 16, no. 4 (August 24, 2013): 1025–38. http://dx.doi.org/10.1007/s11009-013-9366-3.
Повний текст джерелаRachev, S. T., and I. Olkin. "Mass transportation problems with capacity constraints." Journal of Applied Probability 36, no. 2 (June 1999): 433–45. http://dx.doi.org/10.1239/jap/1032374463.
Повний текст джерелаWang, Jiandong, Zhen Wang, Xuan Zhou, and Fan Yang. "Design of delay timers based on estimated probability mass functions of alarm durations." Journal of Process Control 110 (February 2022): 154–65. http://dx.doi.org/10.1016/j.jprocont.2022.01.002.
Повний текст джерелаBelaid, Nawal, Smail Adjabi, Nabil Zougab, and Célestin C. Kokonendji. "Bayesian bandwidth selection in discrete multivariate associated kernel estimators for probability mass functions." Journal of the Korean Statistical Society 45, no. 4 (December 2016): 557–67. http://dx.doi.org/10.1016/j.jkss.2016.04.001.
Повний текст джерелаДисертації з теми "Probability mass functions"
Bayramoglu, Muhammet Fatih. "The Hilbert Space Of Probability Mass Functions And Applications On Probabilistic Inference." Phd thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613613/index.pdf.
Повний текст джерелаKharoufeh, Jeffrey P. "Density estimation for functions of correlated random variables." Ohio : Ohio University, 1997. http://www.ohiolink.edu/etd/view.cgi?ohiou1177097417.
Повний текст джерелаPfister, Mark. "Distribution of a Sum of Random Variables when the Sample Size is a Poisson Distribution." Digital Commons @ East Tennessee State University, 2018. https://dc.etsu.edu/etd/3459.
Повний текст джерелаGreen, Christopher Lee. "IP Algorithm Applied to Proteomics Data." Diss., CLICK HERE for online access, 2004. http://contentdm.lib.byu.edu/ETD/image/etd618.pdf.
Повний текст джерелаGomez, Beltran Liseth Ana Délia. "A interação entre a fertilidade do solo e a massa da semente influencia os atributos funcionais de espécies arbóreas tropicais?" Universidade Federal de São Carlos, 2017. https://repositorio.ufscar.br/handle/ufscar/9380.
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Biological, physical and chemical characteristics of the soil are environmental filters that strongly influence the composition of the plant communities. The knowledge of the effect of soil conditions on the survival and growth of plant species is important for the recovery activities in degraded areas. These aspects of plant performance are directly related to the functional characteristics of species, so understanding the responses of the different resources to different soil conditions can help to choose species that are best suited to each area. We have carried out an experiment in nursery with the objective of evaluating the influence of different soil treatments on survival and functional characteristics; Leaf Area (LA), Specific Leaf Area (SLA), Leaf Dry Matter Content (LDMC), Root Mass Fraction (RMF), Specific Root Length (SRL) and Relative Height Increment (RHI) of eleven native forest species forming a seed mass gradient. The treatments used in the experiment were control soil - without the addition of any fertilizer (CT); addition of chemical fertilizer - NPK (QU); addition of organic fertilizer (OR) and the addition of chemical fertilizer and organic fertilizer (OQ). Soil chemical attributes in the four treatments were evaluated after two and seven months after planting to verify the changes that occurred over time. In addition, we evaluated soil chemical attributes of natural areas of occurrence of these species, preserved and degraded forests. The monitoring of the experiment was performed for four months and at the end of this period we recorded survival and measured the functional characteristics of all species. Chemical soil attributes used in the treatments CT and QU were more similar to the attributes of the areas used as reference, showing higher values of acidity potential (H + Al) and cation exchange capacity (CTC), and lower values of nitrogen (N) and organic matter. The seed mass heavily influenced survival in CT, QU and OR treatments and did not differed between CT and QU treatments and, furthermore, in OR treatment the survival was greater than in CT and QU treatments. The effect of seed mass on survival was not significant in OQ treatment. We detected a high positive correlation between SLA, RMF and SRL that were negatively correlated with LA and RHI. The functional properties of the species differed between treatments, but no differences were detected between treatments OR and OQ. In these two treatments, species reached higher values of LA and RHI and lower values of SRL, RMF and SLA than other treatments. Functional attributes varied between and within species. Phenotypic plasticity was higher in LA, RHI, SRL and RMF, and the variation of LA, RHI and SRL were highly correlated with each other and together were negatively related to seed mass. This study showed that limited terrestrial resources were able to modify root 12 architecture, leaf traits and the rate of growth of the aerial parts, which suggests that plants should invest more in fundraising bodies to increase the chances of survival. Intra-specific variation of LA, RHI, SRL, RHI and LDMC characteristics were correlated with each other and negatively correlated with seed mass. Smaller seed species were more plastic than larger seed species. In the treatment CT, these species reached higher values of SLA and SRL, while treatments with organic matter addition, these species reach higher values of LA and RHI. The addition of organic matter in the soil increased the survival and growth of plants, in particular small seed species. Thus, the addition of organic matter as pre-planting treatment proved to be more efficient to increase the performance of native tree species. However, experiments under field conditions are necessary to quantify the efficacy of manure on the reintroduction of native species into deforested forests.
As características biológicas, físicas e químicas do solo são filtros ambientais que influenciam fortemente a composição de comunidades vegetais. O conhecimento do efeito das condições do solo na sobrevivência e no crescimento de espécies vegetais é de grande importância para atividades de recuperação de áreas degradadas. Tais aspectos do desempenho de plantas estão diretamente relacionados aos traços funcionais das espécies, consequentemente a compreensão das respostas dos diferentes traços a diferentes condições edáficas pode auxiliar na escolha de espécies que se adaptem melhor a cada área. Nós conduzimos um experimento em viveiro com o objetivo de avaliar a influência de diferentes tratamentos de solo na sobrevivência e nos traços funcionais; Área Foliar (AF), Área foliar específica (AFE), Conteúdo de matéria seca foliar (CMSF) Fração da massa da raiz (FMR), Comprimentos especifico da raiz (CER) e Taxa de crescimento em altura (TCA) de onze espécies florestais nativas que formam um gradiente de massa de semente. Os tratamentos usados no experimento foram: solo controle – sem a adição de nenhum tipo de adubo ou fertilizante (CT); adição de fertilizante químico - NPK (QU); adição de adubo orgânico (OR) e adição fertilizante químico e de adubo orgânico (OQ). Os atributos químicos do solo nos quatro tratamentos foram avaliados após dois e sete meses da semeadura para verificar as mudanças ocorridas ao longo do tempo. Além disto, avaliamos os atributos químicos do solo de áreas naturais de ocorrência destas espécies, florestas preservadas e degradadas. O monitoramento do experimento foi conduzido por quatro meses e ao final deste período registramos a sobrevivência e as medidas dos traços funcionais de todas as espécies. Os atributos químicos dos solos usados nos tratamentos Controle e Químico foram mais semelhantes aos atributos das áreas usadas como referência, apresentando maiores valores de acidez potencial (H+Al) e Capacidade de troca catiônica (CTC), e menores valores de Nitrogênio (N) e de matéria orgânica. A massa da semente influenciou fortemente a sobrevivência nos tratamentos CT, QU e OR, e não diferiu entre os tratamentos CT e QU, por outro lado, no tratamento OR a sobrevivência foi maior em comparação com os tratamentos CT e QU. O efeito da massa da semente na sobrevivência não foi significativo no tratamento OQ. Detectamos uma alta correlação positiva entre os traços AFE, FMR e CER que foram negativamente correlacionados com AF e TCA. Os atributos funcionais das espécies diferiram entre os tratamentos, porém não foram detectadas diferenças entre os tratamentos OR e OQ. Nestes dois tratamentos as espécies alcançaram valores mais altos de AF e TCA e valores de 8 CER, FMR e AFE mais baixos do que nos demais tratamentos. Os atributos funcionais variaram entre e dentro de espécies. A plasticidade fenotípica foi maior com relação a AF, TCA, CER e FMR, sendo que a variação de AF, TCA e CER foram altamente correlacionadas entre si e juntas foram negativamente relacionadas com a massa da semente. Este estudo mostrou que a limitação de recursos do solo foi capaz de modificar a arquitetura das raízes, os traços foliares e a taxa de crescimento das partes aéreas, sugerindo que plantas devem investir mais em órgãos de captação de recursos para aumentar as chances de sobrevivência. A variação intraespecífica dos traços AF, TCA, AFE, CER e CMSF foram correlacionados entre si e negativamente correlacionados com a massa da semente. Espécies de sementes menores foram mais plásticas do que espécies de sementes maiores. No tratamento CT estas espécies alcançaram maiores valores de AFE e CER, enquanto que nos tratamentos que receberam adição de matéria orgânica, estas espécies alcançaram maiores valores de AF e TCR. A adição de matéria orgânica ao solo aumentou a sobrevivência e o crescimento das plantas, especialmente das espécies de sementes menores. Nesse sentido, a adição de matéria orgânica como tratamento pré-plantio mostrou ser mais eficiente para aumentar o desempenho de espécies arbóreas nativas. No entanto experimentos sob condições de campo são necessários para quantificar a eficácia do uso de esterco na reintrodução de espécies nativa em florestas desmatadas.
Somé, Sobom Matthieu. "Estimations non paramétriques par noyaux associés multivariés et applications." Thesis, Besançon, 2015. http://www.theses.fr/2015BESA2030/document.
Повний текст джерелаThis work is about nonparametric approach using multivariate mixed associated kernels for densities, probability mass functions and regressions estimation having supports partially or totally discrete and continuous. Some key aspects of kernel estimation using multivariate continuous (classical) and (discrete and continuous) univariate associated kernels are recalled. Problem of supports are also revised as well as a resolution of boundary effects for univariate associated kernels. The multivariate associated kernel is then defined and a construction by multivariate mode-dispersion method is provided. This leads to an illustration on the bivariate beta kernel with Sarmanov's correlation structure in continuous case. Properties of these estimators are studied, such as the bias, variances and mean squared errors. An algorithm for reducing the bias is proposed and illustrated on this bivariate beta kernel. Simulations studies and applications are then performed with bivariate beta kernel. Three types of bandwidth matrices, namely, full, Scott and diagonal are used. Furthermore, appropriated multiple associated kernels are used in a practical discriminant analysis task. These are the binomial, categorical, discrete triangular, gamma and beta. Thereafter, associated kernels with or without correlation structure are used in multiple regression. In addition to the previous univariate associated kernels, bivariate beta kernels with or without correlation structure are taken into account. Simulations studies show the performance of the choice of associated kernels with full or diagonal bandwidth matrices. Then, (discrete and continuous) associated kernels are combined to define mixed univariate associated kernels. Using the tools of unification of discrete and continuous analysis, the properties of the mixed associated kernel estimators are shown. This is followed by an R package, created in univariate case, for densities, probability mass functions and regressions estimations. Several smoothing parameter selections are implemented via an easy-to-use interface. Throughout the paper, bandwidth matrix selections are generally obtained using cross-validation and sometimes Bayesian methods. Finally, some additionnal informations on normalizing constants of associated kernel estimators are presented for densities or probability mass functions
Bailey, Lara. "Deformable Registration to Create Cytoarchitectonic Probability Maps for Functional Analysis of Primary Auditory Cortex." Thesis, 2008. http://hdl.handle.net/1974/1536.
Повний текст джерелаThesis (Master, Computing) -- Queen's University, 2008-09-26 19:50:54.582
Книги з теми "Probability mass functions"
Sharma, Megha. Computing the probability mass function of the maximum flow through a reliable network. Ahmedabad: Indian Institute of Management, 2009.
Знайти повний текст джерелаSchurz, Henri, Philip J. Feinsilver, Gregory Budzban, and Harry Randolph Hughes. Probability on algebraic and geometric structures: International research conference in honor of Philip Feinsilver, Salah-Eldin A. Mohammed, and Arunava Mukherjea, June 5-7, 2014, Southern Illinois University, Carbondale, Illinois. Edited by Mohammed Salah-Eldin 1946- and Mukherjea Arunava 1941-. Providence, Rhode Island: American Mathematical Society, 2016.
Знайти повний текст джерелаHoring, Norman J. Morgenstern. Retarded Green’s Functions. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198791942.003.0005.
Повний текст джерелаHall, Peter. Principal component analysis for functional data. Edited by Frédéric Ferraty and Yves Romain. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199568444.013.8.
Повний текст джерелаVanMarcke, E. H. Quantum Origins of Cosmic Structure: Probability Density Function of Quantity-mass-ratio Logarithm. Swets & Zeitlinger Publishers, 1997.
Знайти повний текст джерелаInformation-Theoretic Methods for Estimating of Complicated Probability Distributions, Volume 207 (Mathematics in Science and Engineering). Elsevier Science, 2006.
Знайти повний текст джерелаЧастини книг з теми "Probability mass functions"
Kay, Steven M. "Conditional Probability Mass Functions." In Intuitive Probability and Random Processes Using MATLAB®, 215–46. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/0-387-24158-2_8.
Повний текст джерелаYi, Pu, Hao Wang, Tao Xie, Darko Marinov, and Wing Lam. "A Theoretical Analysis of Random Regression Test Prioritization." In Tools and Algorithms for the Construction and Analysis of Systems, 217–35. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99527-0_12.
Повний текст джерелаKutílek, Miroslav, Miroslav Krejca, and Jana Kupcová-Vlašimská. "The role of estimation error in probability density function of soil hydraulic parameters: Pedotop scale." In Environmental Mechanics: Water, Mass and Energy Transfer in the Biosphere, 259–63. Washington, D. C.: American Geophysical Union, 2002. http://dx.doi.org/10.1029/129gm21.
Повний текст джерелаJenny, Patrick, and Daniel W. Meyer. "Transported Probability and Mass Density Function (PDF/MDF) Methods for Uncertainty Assessment and Multi-Scale Problems." In Lecture Notes in Computational Science and Engineering, 35–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22061-6_2.
Повний текст джерелаLiu, Hang, Yuyin Ma, Peng Chen, Yunni Xia, Yong Ma, Wanbo Zheng, and Xiaobo Li. "Scheduling Multi-workflows over Edge Computing Resources with Time-Varying Performance, A Novel Probability-Mass Function and DQN-Based Approach." In Web Services – ICWS 2020, 197–209. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59618-7_13.
Повний текст джерелаCsenki, Attila. "The Number of Visits to a Subset of the State Space by an Irreducible Semi-Markov Process during a Finite Time Interval: The Probability Mass Function." In Dependability for Systems with a Partitioned State Space, 179–204. New York, NY: Springer New York, 1994. http://dx.doi.org/10.1007/978-1-4612-2674-1_10.
Повний текст джерелаDonovan, Therese M., and Ruth M. Mickey. "Probability Mass Functions." In Bayesian Statistics for Beginners, 87–107. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198841296.003.0008.
Повний текст джерелаTrappenberg, Thomas P. "Basic probability theory." In Fundamentals of Machine Learning, 121–40. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198828044.003.0006.
Повний текст джерелаEdge, M. D. "Probability and random variables." In Statistical Thinking from Scratch, 38–59. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198827627.003.0005.
Повний текст джерелаEssington, Timothy E. "Random Variables and Probability." In Introduction to Quantitative Ecology, 109–24. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192843470.003.0007.
Повний текст джерелаТези доповідей конференцій з теми "Probability mass functions"
Tan, Choon Peng, Sin Yen Chu, and Wei Yeing Pan. "Finite-order universal portfolios generated by probability mass functions." In INTERNATIONAL CONFERENCE ON MATHEMATICS, ENGINEERING AND INDUSTRIAL APPLICATIONS 2014 (ICoMEIA 2014). AIP Publishing LLC, 2015. http://dx.doi.org/10.1063/1.4915655.
Повний текст джерелаBayramoglu, Muhammet Fatih, and Ali Ozgur Yilmaz. "Factorization of joint probability mass functions into parity check interactions." In 2009 IEEE International Symposium on Information Theory - ISIT. IEEE, 2009. http://dx.doi.org/10.1109/isit.2009.5205262.
Повний текст джерелаManickam, Shivkumar K. "Probability Mass Functions for which Sources have the Maximum Minimum Expected Length." In 2019 National Conference on Communications (NCC). IEEE, 2019. http://dx.doi.org/10.1109/ncc.2019.8732264.
Повний текст джерелаLi, Hewenxuan, and David Chelidze. "Identification of Variable Amplitude Fatigue Loading Based on Bivariate Probability Mass Functions." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-97488.
Повний текст джерелаFatih Bayramoglu, Muhammet, and Ali Ozgur Yilmaz. "A Hilbert space of probability mass functions and applications on the sum-product algorithm." In 2008 5th International Symposium on Turbo Codes and Related Topics. IEEE, 2008. http://dx.doi.org/10.1109/turbocoding.2008.4658722.
Повний текст джерелаWong, Chun Nam, Hong-Zhong Huang, Jingqi Xiong, and Tianyou Hu. "Weibull Distributed Stress-Dependent Strength Analysis of Aeroengine Alloy Using Lagrange Factor Polynomial." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28090.
Повний текст джерелаJeong, D. Y. "Probabilistic Approach to Conditional Probability of Release of Hazardous Materials From Railroad Tank Cars During Accidents." In ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-10872.
Повний текст джерелаWard, Nicholas J., Stephen Ekwaro-Osire, and João Paulo Dias. "Uncertainty Quantification of Mass and Aerodynamic Rotor Imbalance for Offshore Wind Turbines." In ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/gt2020-15792.
Повний текст джерелаYin, Shih-Hsun, and Bogdan I. Epureanu. "High-Sensitivity Mass Sensing Based on Enhanced Nonlinear Dynamics and Attractor Morphing Modes." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-15648.
Повний текст джерелаNieckele, Angela O., Mônica F. Naccache, Marcos S. P. Gomes, João E. Carneiro, and Ricardo Serfaty. "Models Evaluations of Combustion Process in a Cylindrical Furnace." In ASME 2001 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/imece2001/htd-24232.
Повний текст джерелаЗвіти організацій з теми "Probability mass functions"
Daudelin, Francois, Lina Taing, Lucy Chen, Claudia Abreu Lopes, Adeniyi Francis Fagbamigbe, and Hamid Mehmood. Mapping WASH-related disease risk: A review of risk concepts and methods. United Nations University Institute for Water, Environment and Health, December 2021. http://dx.doi.org/10.53328/uxuo4751.
Повний текст джерела