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Relevant bibliographies by topics / Continuous probability distribution

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Academic literature on the topic 'Continuous probability distribution'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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Journal articles on the topic "Continuous probability distribution"

1

Hashim, Hassaneen Abd Aljabar, and Kareema Abed Al-kadim Al-Khafaji. "Composition a Continuous Probability Distribution Resulting from Mixing Two Probability Distributions." Journal of Physics: Conference Series 1804, no. 1 (2021): 012028. http://dx.doi.org/10.1088/1742-6596/1804/1/012028.

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Li, Ye. "Probability Distribution Mapping and Parameter Estimation of Continuous Random Financial Data." Finance and Market 1, no. 1 (2016): 13. http://dx.doi.org/10.18686/fam.v1i1.3.

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<span style="font-family: 'Times New Roman','serif'; font-size: 10.5pt; mso-fareast-font-family: SimSun; mso-font-kerning: 1.0pt; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR;" lang="EN-US">It will certainly obey a probability distribution for any continuous random financial data. If in any period of observation, the observed value of a set of random financial data is finite list, its actual distribution not equal empirical distribution and actual distribution is known but parameters, it is available to estimate the parameters of actual distribution throug

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Zubkov, V. V. "Distribution functions for continuous medium without probability hypotheses." Journal of Physics: Conference Series 1352 (October 2019): 012067. http://dx.doi.org/10.1088/1742-6596/1352/1/012067.

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Tovissodé, Chénangnon Frédéric, Sèwanou Hermann Honfo, Jonas Têlé Doumatè, and Romain Glèlè Kakaï. "On the Discretization of Continuous Probability Distributions Using a Probabilistic Rounding Mechanism." Mathematics 9, no. 5 (2021): 555. http://dx.doi.org/10.3390/math9050555.

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Most existing flexible count distributions allow only approximate inference when used in a regression context. This work proposes a new framework to provide an exact and flexible alternative for modeling and simulating count data with various types of dispersion (equi-, under-, and over-dispersion). The new method, referred to as “balanced discretization”, consists of discretizing continuous probability distributions while preserving expectations. It is easy to generate pseudo random variates from the resulting balanced discrete distribution since it has a simple stochastic representation (pro

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Dimitrijevic, Strahinja, Aleksandar Kostic, and Petar Milin. "Stability of the syntagmatic probability distributions." Psihologija 42, no. 1 (2009): 107–20. http://dx.doi.org/10.2298/psi0901107d.

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The aim of the present study is to establish criteria for the optimal size of a corpus that can provide stable conditional probabilities of morphological and/or syntagmatic types. The optimality of corpus size is defined in terms of the smallest sample that generates probability distribution equal to distribution derived from the large sample that generates stable probabilities. The latter distribution we refer to as 'target distribution'. In order to establish the above criteria we varied the sample size, the word sequence size (bigrams and trigrams), sampling procedure (randomly chosen words

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Ďutková, Silvia, Dominika Hoštáková, Tomáš Mišík, and Iwona Rybicka. "Determination of probability distribution of customer input at post office." Transport and Communications 5, no. 2 (2017): 6–10. http://dx.doi.org/10.26552/tac.c.2017.2.2.

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If we want to analyze a real system with a large number of input data, it is very convenient to determine a probability distribution that best fits to given input data. There are many statistical methods to determine the correct probability distribution and one of them is Chi-Square Goodness of Fit Test. This statistical test can be also used to find out a probability distribution of time intervals between arrivals of customers at post office. Intervals between arrivals of customers occur in continuous time and therefore we consider continuous probable distributions.

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Roychowdhury, Mrinal Kanti, and Wasiela Salinas. "Quantization for a Mixture of Uniform Distributions Associated with Probability Vectors." Uniform distribution theory 15, no. 1 (2020): 105–42. http://dx.doi.org/10.2478/udt-2020-0006.

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AbstractThe basic goal of quantization for probability distribution is to reduce the number of values, which is typically uncountable, describing a probability distribution to some finite set and thus approximation of a continuous probability distribution by a discrete distribution. Mixtures of probability distributions, also known as mixed distributions, are an exciting new area for optimal quantization. In this paper, we investigate the optimal quantization for three different mixed distributions generated by uniform distributions associated with probability vectors.

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Farnsworth, David L. "The Most Compact Subdomain of a Continuous Probability Distribution." Teaching Statistics 26, no. 3 (2004): 81–83. http://dx.doi.org/10.1111/j.1467-9639.2004.00175.x.

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Hassairi, Abdelhamid, and Ons Regaieg. "On the Tukey depth of a continuous probability distribution." Statistics & Probability Letters 78, no. 15 (2008): 2308–13. http://dx.doi.org/10.1016/j.spl.2008.02.008.

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Puente, Carlos E., Miguel M. López, Jorge E. Pinzón, and José M. Angulo. "The Gaussian distribution revisited." Advances in Applied Probability 28, no. 02 (1996): 500–524. http://dx.doi.org/10.1017/s000186780004859x.

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A new construction of the Gaussian distribution is introduced and proven. The procedure consists of using fractal interpolating functions, with graphs having increasing fractal dimensions, to transform arbitrary continuous probability measures defined over a closed interval. Specifically, let X be any probability measure on the closed interval I with a continuous cumulative distribution. And let f Θ,D :I → R be a deterministic continuous fractal interpolating function, as introduced by Barnsley (1986), with parameters Θ and fractal dimension for its graph D. Then, the derived measure Y = f Θ,D

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Dissertations / Theses on the topic "Continuous probability distribution"

1

Ackerley, Elizabeth. "Statistical modelling of continuous distributions with a finite probability of zeros." Thesis, Lancaster University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.289034.

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Sitton, David E. R. "Generating random absolutely continuous distributions." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/28989.

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Chang, Shu-Ching. "Antedependence Models for Skewed Continuous Longitudinal Data." Diss., University of Iowa, 2013. https://ir.uiowa.edu/etd/4827.

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This thesis explores the problems of fitting antedependence (AD) models and partial antecorrelation (PAC) models to continuous non-Gaussian longitudinal data. AD models impose certain conditional independence relations among the measurements within each subject, while PAC models characterize the partial correlation relations. The models are parsimonious and useful for data exhibiting time-dependent correlations. Since the relation of conditional independence among variables is rather restrictive, we first consider an autoregressively

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NADIMPALLI, GAYATRI. "ESTIMATING LEAKS IN WATER DISTRIBUTION SYSTEMS BY SEQUENTIAL STATISTICAL ANALYSIS OF CONTINUOUS FLOW READINGS." University of Cincinnati / OhioLINK, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1068674771.

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Huschens, Stefan. "Stetigkeit in der Statistik." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-222568.

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Andrews, Zoe Helen. "Continuous probability distributions in model-based specification languages." Thesis, University of Newcastle Upon Tyne, 2012. http://hdl.handle.net/10443/1696.

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Model-based specification languages provide a means for obtaining assurance of dependability of complex computer-based systems, but provide little support for modelling and analysing fault behaviour, which is inherently probabilistic in nature. In particular, the need for a detailed account of the role of continuous probability has been largely overlooked. This thesis addresses the role of continuous probability in model-based specification languages. A model-based specification language (sGCL) that supports continuous probability distributions is studied. The use of sGCL and how it interacts

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Bekker, Leonid. "Association between mean residual life (MRL) and failure rate functions for continuous and discrete lifetime distributions." FIU Digital Commons, 2002. http://digitalcommons.fiu.edu/etd/1479.

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The purpose of this study was to correct some mistakes in the literature and derive a necessary and sufficient condition for the MRL to follow the roller-coaster pattern of the corresponding failure rate function. It was also desired to find the conditions under which the discrete failure rate function has an upside-down bathtub shape if corresponding MRL function has a bathtub shape. The study showed that if discrete MRL has a bathtub shape, then under some conditions the corresponding failure rate function has an upside-down bathtub shape. Also the study corrected some mistakes in proofs of

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Yu, Zhe. "A Continuous Analog of Run Length Distributions Reflecting Accumulated Fractionation Events." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/35256.

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We propose a new, continuous model of the fractionation process (duplicate gene deletion after polyploidization) on the real line. The aim is to infer how much DNA is deleted at a time, based on segment lengths for alternating deleted (invisible) and undeleted (visible) regions. After deriving a number of analytical results for "one-sided" fractionation, we undertake a series of simulations that help us identify the distribution of segment lengths as a gamma with shape and rate parameters evolving over time. This leads to an inference procedure based on observed length distributions for visi

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Cavalcanti, Gilmara Alves. "Estimação de valores estatísticos de referência para as internações por condições sensíveis a atenção primária em municípios brasileiros." Universidade Federal da Paraíba, 2017. http://tede.biblioteca.ufpb.br:8080/handle/tede/9019.

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Submitted by Viviane Lima da Cunha (viviane@biblioteca.ufpb.br) on 2017-06-26T11:50:59Z No. of bitstreams: 1 arquivototal.pdf: 7515806 bytes, checksum: a09d41d012f6b4bd6ac4e7f7ffd37975 (MD5)<br>Made available in DSpace on 2017-06-26T11:50:59Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 7515806 bytes, checksum: a09d41d012f6b4bd6ac4e7f7ffd37975 (MD5) Previous issue date: 2017-03-22<br>Many indicators have been used to verify the e ciency and quality of services in primary health care. Recently, this level of attention has been evaluated in Brazil. The ambulatory cary sensitive conditions (

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Golder, Jacques. "Modélisation d'un phénomène pluvieux local et analyse de son transfert vers la nappe phréatique." Phd thesis, Université d'Avignon, 2013. http://tel.archives-ouvertes.fr/tel-01057725.

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Dans le cadre des recherches de la qualité des ressources en eau, l'étude du processus de transfert de masse du sol vers la nappe phréatique constitue un élément primordial pour la compréhension de la pollution de cette dernière. En effet, les éléments polluants solubles à la surface (produits liés aux activités humaines tels engrais, pesticides...) peuvent transiter vers la nappe à travers le milieu poreux qu'est le sol. Ce scénario de transfert de pollution repose sur deux phénomènes : la pluie qui génère la masse d'eau à la surface et la dispersion de celle-ci à travers le milieu poreux. La

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Books on the topic "Continuous probability distribution"

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Samuel, Kotz, and Balakrishnan N. 1956-, eds. Continuous univariate distributions. 2nd ed. Wiley, 1994.

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D, Lai C., ed. The engineering statistician's guide to continuous bivariate distributions. Rumsby Scientific Pub., 1991.

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Tsai, Hsien-Tang. A 3-interval polynomial approximation for continuous univariate distribution functions. Institute for Research in the Behavioral, Economic, and Management Sciences, Krannert Graduate School of Management, Purdue University, 1986.

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4

Thomas, A. W. Computer programs for analysis and simulation of seasonally continuous probability distributions. Southern Piedmont Conservation Research Center, Agricultural Research Service, USDA, 1987.

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5

Yin, G. George. Continuous-Time Markov Chains and Applications: A Singular Perturbation Approach. Springer New York, 1998.

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Costa, Oswaldo L. V. Continuous-Time Markov Jump Linear Systems. Springer Berlin Heidelberg, 2013.

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Oswaldo Luiz do Valle Costa. Continuous Average Control of Piecewise Deterministic Markov Processes. Springer New York, 2013.

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Yin, George. Continuous-Time Markov Chains and Applications: A Two-Time-Scale Approach. 2nd ed. Springer New York, 2013.

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David, Bakstein, and SpringerLink (Online service), eds. An Introduction to Continuous-Time Stochastic Processes: Theory, Models, and Applications to Finance, Biology, and Medicine. 2nd ed. Birkhäuser Boston, 2012.

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Jikov, V. V. Homogenization of Differential Operators and Integral Functionals. Springer Berlin Heidelberg, 1994.

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Book chapters on the topic "Continuous probability distribution"

1

Mariappan, Perumal. "Continuous Probability Distribution: Normal Distribution." In Statistics for Business. Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9780429443244-11.

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2

Roe, Byron P. "The Normal (or Gaussian) Distribution and Other Continuous Distributions." In Probability and Statistics in Experimental Physics. Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4684-9296-5_6.

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Roe, Byron P. "The Normal (or Gaussian) Distribution and Other Continuous Distributions." In Probability and Statistics in Experimental Physics. Springer New York, 1992. http://dx.doi.org/10.1007/978-1-4757-2186-7_6.

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Roe, Byron P. "The Normal (or Gaussian) Distribution and Other Continuous Distributions." In Probability and Statistics in the Physical Sciences. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-53694-7_6.

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Kozak, A., R. A. Kozak, C. L. Staudhammer, and S. B. Watts. "Continuous distributions and the normal distribution: describing data that are measured." In Introductory probability and statistics: applications for forestry and natural sciences. CABI, 2019. http://dx.doi.org/10.1079/9781789243307.0093.

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Kozak, A., R. A. Kozak, C. L. Staudhammer, and S. B. Watts. "Continuous distributions and the normal distribution: describing data that are measured." In Introductory probability and statistics: applications for forestry and natural sciences. CABI, 2019. http://dx.doi.org/10.1079/9781845932756.0093.

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Thomopoulos, Nick T. "Continuous Distributions." In Probability Distributions. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76042-1_1.

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Pitman, Jim. "Continuous Distributions." In Probability. Springer New York, 1993. http://dx.doi.org/10.1007/978-1-4612-4374-8_4.

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O’Hagan, Anthony. "Continuous distributions." In Probability. Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-1211-3_7.

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Pitman, Jim. "Continuous Joint Distributions." In Probability. Springer New York, 1993. http://dx.doi.org/10.1007/978-1-4612-4374-8_5.

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Conference papers on the topic "Continuous probability distribution"

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Eidukas, Danielius, Rimantas Kalnius, and Anicetas Vaisvila. "Probability Distribution Transformation in Continuous Information Systems Control." In 2007 29th International Conference on Information Technology Interfaces. IEEE, 2007. http://dx.doi.org/10.1109/iti.2007.4283841.

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Zhao, Sicheng, Hongxun Yao, and Xiaolei Jiang. "Predicting Continuous Probability Distribution of Image Emotions in Valence-Arousal Space." In MM '15: ACM Multimedia Conference. ACM, 2015. http://dx.doi.org/10.1145/2733373.2806354.

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Qiu, Meikang, Jiande Wu, Fei Hu, Shaobo Liu, and Lingfeng Wang. "Voltage Assignment for Soft Real-Time Embedded Systems with Continuous Probability Distribution." In 2009 15th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA). IEEE, 2009. http://dx.doi.org/10.1109/rtcsa.2009.50.

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Gordillo, Christian Arcos, J. R. Boisson de Marca, and Abraham Alcaim. "Median filtering the temporal probability distribution in histogram mapping for robust continuous speech recognition." In 2016 24th European Signal Processing Conference (EUSIPCO). IEEE, 2016. http://dx.doi.org/10.1109/eusipco.2016.7760438.

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Canu, Romain, Christophe Dumouchel, Benjamin Duret, et al. "Where does the drop size distribution come from?" In ILASS2017 - 28th European Conference on Liquid Atomization and Spray Systems. Universitat Politècnica València, 2017. http://dx.doi.org/10.4995/ilass2017.2017.4706.

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This study employs DNS of two-phase flows to enhance primary atomization understanding and modelling to beused in numerical simulation in RANS or LES framework. In particular, the work has been aimed at improving the information on the liquid-gas interface evolution available inside the Eulerian-Lagrangian Spray Atomization (ELSA) framework. Even though this approach has been successful to describe the complete liquid atomization process from the primary region to the dilute spray, major improvements are expected on the establishment of the drop size distribution (DSD). Indeed, the DSD is easi

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Rook, Todd. "Transient and Steady-State Stochastic Analysis of Nonlinear Oscillators Using the Fokker-Planck-Kolmonogrov Equation." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85029.

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An efficient technique to calculate the transient and stationary probability distribution functions (PDF) of the response of SDOF oscillators with piecewise continuous nonlinearities is presented. The method compares favorably with previous methods in reproducing stationary distributions and chaotic attractors, but further work is needed in calculating Lyapunov exponents to the desired accuracy.

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Szynal, Dominik. "Goodness-of-fit tests derived from characterizations of continuous distributions." In Stability in Probability. Institute of Mathematics Polish Academy of Sciences, 2010. http://dx.doi.org/10.4064/bc90-0-14.

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Tao, Shanshan, Jialing Song, Zhifeng Wang, Yong Liu, and Sheng Dong. "Statistical Analysis for the Duration and Time Intervals of Tropical Cyclones, Hong Kong." In ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/omae2019-95791.

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Abstract Hong Kong is impacted by tropical cyclones from April to December each year. The duration of tropical cyclones is one key factor to impact the normal operation of port or coastal engineering, and longer time interval between two tropical cyclones can provide longer operation or construction time. Therefore, it is quite important to study on the long-term laws of the duration and time intervals of tropical cyclones which attacked Hong Kong. The Hong Kong Observatory issues the warning signals to warn the public of the threat of winds associated with a tropical cyclone. Choose the tropi

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Chen, Zhen, Tangbin Xia, and Ershun Pan. "Remaining Useful Life Estimation Based on a Segmental Hidden Markov Model With Continuous Observations." In ASME 2017 12th International Manufacturing Science and Engineering Conference collocated with the JSME/ASME 2017 6th International Conference on Materials and Processing. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/msec2017-2765.

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In this paper, a segmental hidden Markov model (SHMM) with continuous observations, is developed to tackle the problem of remaining useful life (RUL) estimation. The proposed approach has the advantage of predicting the RUL and detecting the degradation states simultaneously. As the observation space is discretized into N segments corresponding to N hidden states, the explicit relationship between actual degradation paths and the hidden states can be depicted. The continuous observations are fitted by Gaussian, Gamma and Lognormal distribution, respectively. To select a more suitable distribut

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Shahan, David W., Peter B. Backlund, and Carolyn C. Seepersad. "Classifier-Guided Sampling for Discrete Variable, Discontinuous Design Space Exploration." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-13138.

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Estimation of density algorithms (EDAs) have been developed for optimization of discrete, continuous, or mixed discrete and continuous simulation-based design problems. EDAs construct a probability distribution on the set of highest performing designs and sample the distribution for the next generation of solutions. In previous work, the authors have demonstrated how classifier-guided sampling can also be used for discrete variable, discontinuous design space exploration. In this paper we develop the rationale for using classifier-guided sampling as a simple step beyond EDAs that not only impr

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