Relevant bibliographies by topics / Statistic and probability

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Statistic and probability'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Statistic and probability"

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Driscoll, Michale F., and W. D. Laigh. "Characterizations and o-statistic representations of lu-statistics." Communications in Statistics - Theory and Methods 17, no. 8 (1988): 2763–77. http://dx.doi.org/10.1080/03610928808829769.

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Long, Michael A., Kenneth J. Berry, and Paul W. Mielke. "Multiway Contingency Tables: Monte Carlo Resampling Probability Values for the Chi-Squared and Likelihood-Ratio Tests." Psychological Reports 107, no. 2 (2010): 501–10. http://dx.doi.org/10.2466/03.pr0.107.5.501-510.

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Monte Carlo resampling methods to obtain probability values for chi-squared and likelihood-ratio test statistics for multiway contingency tables are presented. A resampling algorithm provides random arrangements of cell frequencies in a multiway contingency table, given fixed marginal frequency totals. Probability values are obtained from the proportion of resampled test statistic values equal to or greater than the observed test statistic value.
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Kudlaev, E. M. "Separable statistics derived from a given separable statistic by “restricting” the probability space." Journal of Mathematical Sciences 81, no. 4 (1996): 2824–29. http://dx.doi.org/10.1007/bf02362487.

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Jäntschi, Lorentz, and Sorana D. Bolboacă. "Computation of Probability Associated with Anderson–Darling Statistic." Mathematics 6, no. 6 (2018): 88. http://dx.doi.org/10.3390/math6060088.

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Oni Yuliani, Oni. "The Teaching Statistic Using Matlab." KURVATEK 4, no. 2 (2019): 1–10. http://dx.doi.org/10.33579/krvtk.v4i2.1193.

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This paper is to describe the use of Matlab as a scientific tool for the teaching of statistics in undergraduate school. Application of this software in the teaching of some difficult topics like probability concepts, probability distribution, statistical significance, and significance tests, were demonstrated using the Matlab. Matlab has pro­ved it­self to be a ve­ry ef­fec­ti­ve to­ol in the edu­ca­tio­nal pro­cess be­cau­se it of­fers a sim­ple and po­wer­ful to­ol for ana­ly­zing and vi­su­a­li­zing re­sults of nu­me­ri­cal si­mu­la­tions and me­a­sure­ments.
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Pacini, David. "Proximal statistic: Asymptotic normality." Statistics & Probability Letters 167 (December 2020): 108896. http://dx.doi.org/10.1016/j.spl.2020.108896.

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LaBudde, Robert A., and James Harnly. "Probability of Identification: A Statistical Model for the Validation of Qualitative Botanical Identification Methods." Journal of AOAC INTERNATIONAL 95, no. 1 (2012): 273–85. http://dx.doi.org/10.5740/jaoacint.11-266.

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Abstract A qualitative botanical identification method (BIM) is an analytical procedure that returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer, or regulator to determine whether a botanical material being tested is the same as the target (desired) material, or whether it contains excessive nontarget (undesirable) material. The report describes the development and validation of studies for a BIM based on the proportion of replicates identified, or probability of identification (POI), as the basic observed statistic. The statistical procedures proposed for data analysis follow closely those of the probability of detection, and harmonize the statistical concepts and parameters between quantitative and qualitative method validation. Use of POI statistics also harmonizes statistical concepts for botanical, microbiological, toxin, and other analyte identification methods that produce binary results. The POI statistical model provides a tool for graphical representation of response curves for qualitative methods, reporting of descriptive statistics, and application of performance requirements. Single collaborator and multicollaborative study examples are given.
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CHEN, ZHENMIN, and CHUNMIAO YE. "AN ALTERNATIVE TEST FOR UNIFORMITY." International Journal of Reliability, Quality and Safety Engineering 16, no. 04 (2009): 343–56. http://dx.doi.org/10.1142/s0218539309003435.

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Improving power of goodness-of-fit tests is an important research topic in statistics. The goal of the goodness-of-fit test is to check whether the underlying probability distribution, from which a sample is drawn, differs from a hypothesized distribution. Numerous research papers have been published in this area. It has been shown that the power of the existing goodness-of-fit tests in the literature is unsatisfactory when the alternative distributions are of V-shape or when the sample sizes are small. This motivates the development of more powerful test statistics. In this research, a new test statistic is proposed. The result can be used to test whether the underlying probability distribution differs from a uniform distribution. By applying the probability integral transformation, the proposed test statistic can be used to check whether the underlying distribution differs from any hypothesized distribution. The performance of the method proposed in this research is compared with the Kolmogorov–Smirnov test, which is a widely adopted statistical test in the literature. It has been shown that the test proposed in this proposal is more powerful than the Kolmogorov–Smirnov test in some cases.
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Gladkiy, E. G. "Jacobi probability distribution for approximation of emperic statistic distributions." Technical mechanics 2017, no. 1 (2017): 107–22. http://dx.doi.org/10.15407/itm2017.01.107.

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Hassainia, Farid, Dominique Petit, and Jacques Montplaisir. "Significance probability mapping: The final touch int-statistic mapping." Brain Topography 7, no. 1 (1994): 3–8. http://dx.doi.org/10.1007/bf01184832.

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Dissertations / Theses on the topic "Statistic and probability"

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Forgo, Vincent Z. Mr. "A Distribution of the First Order Statistic When the Sample Size is Random." Digital Commons @ East Tennessee State University, 2017. https://dc.etsu.edu/etd/3181.

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Statistical distributions also known as probability distributions are used to model a random experiment. Probability distributions consist of probability density functions (pdf) and cumulative density functions (cdf). Probability distributions are widely used in the area of engineering, actuarial science, computer science, biological science, physics, and other applicable areas of study. Statistics are used to draw conclusions about the population through probability models. Sample statistics such as the minimum, first quartile, median, third quartile, and maximum, referred to as the five-number summary, are examples of order statistics. The minimum and maximum observations are important in extreme value theory. This paper will focus on the probability distribution of the minimum observation, also known as the first order statistic, when the sample size is random.
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Odei, James Beguah. "Statistical Modeling, Exploration, and Visualization of Snow Water Equivalent Data." DigitalCommons@USU, 2014. https://digitalcommons.usu.edu/etd/3871.

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Due to a continual increase in the demand for water as well as an ongoing regional drought, there is an imminent need to monitor and forecast water resources in the Western United States. In particular, water resources in the IntermountainWest rely heavily on snow water storage. Thus, the need to improve seasonal forecasts of snowpack and considering new techniques would allow water resources to be more effectively managed throughout the entire water-year. Many available models used in forecasting snow water equivalent (SWE) measurements require delicate calibrations. In contrast to the physical SWE models most commonly used for forecasting, we offer a statistical model. We present a data-based statistical model that characterizes seasonal snow water equivalent in terms of a nested time-series, with the large scale focusing on the inter-annual periodicity of dominant signals and the small scale accommodating seasonal noise and autocorrelation. This model provides a framework for independently estimating the temporal dynamics of SWE for the various snow telemetry (SNOTEL) sites. We use SNOTEL data from ten stations in Utah over 34 water-years to implement and validate this model. This dissertation has three main goals: (i) developing a new statistical model to forecast SWE; (ii) bridging existing R packages into a new R package to visualize and explore spatial and spatio-temporal SWE data; and (iii) applying the newly developed R package to SWE data from Utah SNOTEL sites and the Upper Sheep Creek site in Idaho as case studies.
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Galijasevic, Amar, and Josef Tegbaru. "Can IPO first day returns be predicted? A multiple linear regression analysis." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254293.

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During the last three years the Swedish stock market has showed a strong upwards movement from the lows of 2016. At the same time the IPO activity has been large and a lot of the offerings have had a positive return during the first day of trading in the market. The goal of this study is to analyze if there is any particular IPO specific data that has a correlation with the first day return and if it can be used to predict the first day return for future IPO’s. If any regressors were shown to have correlation with the first day return, the goal is also to find a subset of regressors with even higher predictability. Then to classify which regressors show the highest correlation with a large positive return. The method which has been used is a multiple linear regression with IPO-data from the period 2017-2018. The results from the study imply that none of the chosen regressors show any significant correlation with the first day return. It is a complicated process which might be difficult to simplify and quantify into a regression model, but further studies are needed to draw a conclusion if there are any other qualitative factors which correlate with the first day return.<br>Under de senaste tre åren har den svenska aktiemarknaden visat en kraftigt uppåtgående rörelse från de låga nivåerna 2016. Samtidigt har det varit hög IPO-aktivitet, där många noteringar har haft en positiv avkastning under den första handelsdagen. Målet med denna studie är att analysera om det finns särskilda IPO-specifika faktorer som påvisar samband med avkastningen från första handelsdagen och om det kan användas för att förutsäga utvecklingen under första handelsdagen för framtida noteringar. Om regressorerna visade korrelation är målet sedan att ta fram de bästa av dessa för att se om det ökar modellens säkerhet. Vidare var det av intresse att visa vilka regressorer som korrelerar med en positiv avkastning. Metoden som användes var en multipel linjär regression med historisk data från perioden 2017-2018. Studiens resultat visar att ingen av de valda regressorerna har någon signifikant korrelation med avkastningen under första handelsdagen. Börsintroduktioner är komplicerade processer som kan vara svåra att förenkla och kvantifiera i en regressionsmodell, men ytterligare studier behövs för att dra en slutsats om det finns andra kvalitativa faktorer som kan förklara utvecklingen under första handelsdagen.
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Echavarria, Gregory Maria Angelica. "Predictive Data-Derived Bayesian Statistic-Transport Model and Simulator of Sunken Oil Mass." Scholarly Repository, 2010. http://scholarlyrepository.miami.edu/oa_dissertations/471.

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Sunken oil is difficult to locate because remote sensing techniques cannot as yet provide views of sunken oil over large areas. Moreover, the oil may re-suspend and sink with changes in salinity, sediment load, and temperature, making deterministic fate models difficult to deploy and calibrate when even the presence of sunken oil is difficult to assess. For these reasons, together with the expense of field data collection, there is a need for a statistical technique integrating limited data collection with stochastic transport modeling. Predictive Bayesian modeling techniques have been developed and demonstrated for exploiting limited information for decision support in many other applications. These techniques brought to a multi-modal Lagrangian modeling framework, representing a near-real time approach to locating and tracking sunken oil driven by intrinsic physical properties of field data collected following a spill after oil has begun collecting on a relatively flat bay bottom. Methods include (1) development of the conceptual predictive Bayesian model and multi-modal Gaussian computational approach based on theory and literature review; (2) development of an object-oriented programming and combinatorial structure capable of managing data, integration and computation over an uncertain and highly dimensional parameter space; (3) creating a new bi-dimensional approach of the method of images to account for curved shoreline boundaries; (4) confirmation of model capability for locating sunken oil patches using available (partial) real field data and capability for temporal projections near curved boundaries using simulated field data; and (5) development of a stand-alone open-source computer application with graphical user interface capable of calibrating instantaneous oil spill scenarios, obtaining sets maps of relative probability profiles at different prediction times and user-selected geographic areas and resolution, and capable of performing post-processing tasks proper of a basic GIS-like software. The result is a predictive Bayesian multi-modal Gaussian model, SOSim (Sunken Oil Simulator) Version 1.0rc1, operational for use with limited, randomly-sampled, available subjective and numeric data on sunken oil concentrations and locations in relatively flat-bottomed bays. The SOSim model represents a new approach, coupling a Lagrangian modeling technique with predictive Bayesian capability for computing unconditional probabilities of mass as a function of space and time. The approach addresses the current need to rapidly deploy modeling capability without readily accessible information on ocean bottom currents. Contributions include (1) the development of the apparently first pollutant transport model for computing unconditional relative probabilities of pollutant location as a function of time based on limited available field data alone; (2) development of a numerical method of computing concentration profiles subject to curved, continuous or discontinuous boundary conditions; (3) development combinatorial algorithms to compute unconditional multimodal Gaussian probabilities not amenable to analytical or Markov-Chain Monte Carlo integration due to high dimensionality; and (4) the development of software modules, including a core module containing the developed Bayesian functions, a wrapping graphical user interface, a processing and operating interface, and the necessary programming components that lead to an open-source, stand-alone, executable computer application (SOSim - Sunken Oil Simulator). Extensions and refinements are recommended, including the addition of capability for accepting available information on bathymetry and maybe bottom currents as Bayesian prior information, the creation of capability of modeling continuous oil releases, and the extension to tracking of suspended oil (3-D).
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Ministr, Martin. "Matematický model výskytu závad na vybraných stanicích montážní linky motorů." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2008. http://www.nusl.cz/ntk/nusl-228263.

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The quality and the defectiveness of production are important factors in all sectors of engineering industry. On their improve there are a lot of effective tools, descriptive statistics is one of them. Descriptive statistic has many applicable tools but this work primarily focuses on desription of production using time series plot, testing of statistical hypothesis, testing of mutual dependencies of particular defects and control diagrams drawing. It is about a project that connects practice with theory.
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Philippe, Anne. "Contribution à la théorie des lois de référence et aux méthodes de Monte Carlo." Rouen, 1997. http://www.theses.fr/1997ROUES005.

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Cette thèse est composée de deux parties distinctes : la première relève de la statistique bayésienne et la seconde des méthodes de Monte Carlo. Nous étudions, dans la première partie, l'apport des lois non informatives de référence. Nous obtenons, via ces lois et les régions de confiance bayésiennes, une solution au classique problème de Fieller-Creasy posé par le modèle de calibration. Un deuxième problème est l'estimation de fonctions quadratiques d'une moyenne normale. Il conduit à de surprenantes complications dans les inférences bayésiennes et fréquentistes. Nous évaluons les propriétés de ces lois et plus particulièrement leurs propriétés de couverture pour ce modèle. La seconde partie de cette thèse est consacrée à l'estimation des intégrales par les méthodes de Monte Carlo. Nous introduisons un estimateur de Monte Carlo basé sur les propriétés des sommes de Riemann. Nous montrons que cet estimateur possède des propriétés de convergence supérieures aux approches classiques. Nous montrons que la méthode d'échantillonnage pondéré se généralise à notre estimateur et produit un estimateur optimal en terme de réduction de la variance. Nous généralisons notre estimateur aux méthodes de Monte Carlo par chaines de Markov. De plus, nous établissons un critère de contrôle de convergence des chaines de Markov issues des algorithmes de Monte Carlo par chaines de Markov. L'étape de simulation des variables aléatoires, qui apparait dans les méthodes de Monte Carlo, est abordée dans notre étude des lois gamma tronquées. Nous déterminons des algorithmes d'acceptation-rejet dominant les approches classiques. Nous avons illustré les différents résultats obtenus par de nombreuses simulations.
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Morais, Sílvia Cristina Dorneles de. "“EXCEL: uma alternativa para o ensino de probabilidade e estatística”." Universidade Federal de Goiás, 2016. http://repositorio.bc.ufg.br/tede/handle/tede/6381.

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Submitted by Cássia Santos (cassia.bcufg@gmail.com) on 2016-10-11T10:31:41Z No. of bitstreams: 2 Dissertação - Silvia Cristina Dorneles de Morais - 2016.pdf: 2108011 bytes, checksum: 4f95066b3d4fd9191a716470ccfbdfb4 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)<br>Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2016-10-11T11:40:43Z (GMT) No. of bitstreams: 2 Dissertação - Silvia Cristina Dorneles de Morais - 2016.pdf: 2108011 bytes, checksum: 4f95066b3d4fd9191a716470ccfbdfb4 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)<br>Made available in DSpace on 2016-10-11T11:40:43Z (GMT). No. of bitstreams: 2 Dissertação - Silvia Cristina Dorneles de Morais - 2016.pdf: 2108011 bytes, checksum: 4f95066b3d4fd9191a716470ccfbdfb4 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2016-09-30<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES<br>In that work was realized a short analysis of challenges of Maths' education in the High School, in special probability and statistics, that refer to adequation of new technologys availables, distinguishing the difficults found to insert computationals resources in the classroom's every day. We emphasize the using electronics spreadsheets, in that case, Excel like a tool good to learn probability and statistic, searching to balance work's teacher to objectives presents in the Nationals Curriculums Parameters (NCP) and in the new National Common Base Curricular (NCBC), which is in the final process of elaboration. By a research with IFG's teachers, we notice that, although having access to informatics laboratories adequated to education, almost teachers do not use them. Before this situation noticed, we propose some simple activities created with the objective to connective theory from didatics books with the use of electronics spreadsheets, trying to contribute for critical formation of students.<br>Nesse trabalho foi realizada uma breve análise dos desafios do ensino da matemática no Ensino Médio, em especial da probabilidade e estatística, no que se refere à adequação às novas tecnologias disponíveis, salientando as dificuldades encontradas ao inserir recursos computacionais no cotidiano da sala de aula. Enfatizamos a utilização de planilhas eletrônicas, nesse caso do Excel, como uma ferramenta benéfica ao ensino de probabilidade e estatística na busca de adequar o trabalho docente aos objetivos propostos nos Parâmetros Curriculares Nacionais (PCN's) e na nova Base Nacional Curricular Comum (BNCC), que se encontra em fase final de elaboração. Através de um questionário aplicado junto a professores do IFG, constatamos que, mesmo tendo acesso a laboratórios de informática adequados ao ensino, a maioria dos professores não faz uso dos mesmos. Diante da situação vivenciada propomos algumas atividades simples, elaboradas com o objetivo de aliar a teoria estudada nos livros didáticos e a utilização de planilhas eletrônicas, procurando assim contribuir para uma formação crítica dos alunos.
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Lu, Yinghua. "Empirical Likelihood Inference for the Accelerated Failure Time Model via Kendall Estimating Equation." Digital Archive @ GSU, 2010. http://digitalarchive.gsu.edu/math_theses/76.

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In this thesis, we study two methods for inference of parameters in the accelerated failure time model with right censoring data. One is the Wald-type method, which involves parameter estimation. The other one is empirical likelihood method, which is based on the asymptotic distribution of likelihood ratio. We employ a monotone censored data version of Kendall estimating equation, and construct confidence intervals from both methods. In the simulation studies, we compare the empirical likelihood (EL) and the Wald-type procedure in terms of coverage accuracy and average length of confidence intervals. It is concluded that the empirical likelihood method has a better performance. We also compare the EL for Kendall’s rank regression estimator with the EL for other well known estimators and find advantages of the EL for Kendall estimator for small size sample. Finally, a real clinical trial data is used for the purpose of illustration.
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Le, cousin Jean-Maxime. "Asymptotique des feux rares dans le modèle des feux de forêts." Thesis, Paris Est, 2015. http://www.theses.fr/2015PESC1018/document.

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Dans cette thèse, nous nous intéressons à deux modèles de feux de forêts définis sur Z. On étudie le modèle des feux de forêts sur Z avec propagation non instantanée dans le chapitre 2. Dans ce modèle, chaque site a trois états possibles : vide, occupé ou en feu. Un site vide devient occupé avec taux 1. Sur chaque site, des allumettes tombent avec taux λ. Si le site est occupé, il brûle pendant un temps exponentiel de paramètre π avant de se propager à ses deux voisins. S’ils sont eux-mêmes occupés, ils brûlent, sinon le feu s’éteint. On étudie l’asymptotique des feux rares c’est à dire la limite du processus lorsque λ → 0 et π → ∞. On montre qu’il y a trois catégories possibles de limites d’échelles, selon le régime dans lequel λ tend vers 0 et π vers l’infini. On étudie formellement et brièvement dans le chapitre 3 le modèle des feux de forêts sur Z en environnement aléatoire. Dans ce modèle, chaque site n’a que deux états possibles : vide ou occupé. On se donne un paramètre λ &gt; 0, une loi ν sur (0 ,∞) et une suite (κi)i∈Z de variables aléatoires indépendantes identiquement distribuées selon ν. Un site vide i devient occupé avec taux κi. Sur chaque site, des allumettes tombent avec taux λ et détruisent immédiatement la composante de sites occupés correspondante. On étudie l’asymptotique des feux rares. Sous une hypothèse raisonnable sur ν, on espère que le processus converge, avec une renormalisation correcte, vers un modèle limite. On s’attend à distinguer trois processus limites différents<br>The aim of this work is to study two differents forest-fire processes defined on Z. In Chapter 2, we study the so-called one dimensional forest-fire process with non instantaeous propagation. In this model, each site has three possible states: ’vacant’, ’occupied’ or ’burning’. Vacant sites become occupied at rate 1. At each site, ignition (by lightning) occurs at rate λ. When a site is ignited, a fire starts and propagates to neighbors at rate π. We study the asymptotic behavior of this process as λ → 0 and π → ∞. We show that there are three possible classes of scaling limits, according to the regime in which λ → 0 and π → ∞. In Chapter 3, we study formally and briefly the so-called one dimensional forest-fire processes in random media. Here, each site has only two possible states: ’vacant’ or occupied’. Consider a parameter λ &gt; 0, a probability distribution ν on (0 ,∞) as well as (κi)i∈Z an i.i.d. sequence of random variables with law ν. A vacant site i becomes occupied at rate κi. At each site, ignition (by lightning) occurs at rate λ. When a site is ignited, the fire destroys the corresponding component of occupied sites. We study the asymptotic behavior of this process as λ → 0. Under some quite reasonable assumptions on the law ν, we hope that the process converges, with a correct normalization, to a limit forest fire model. We expect that there are three possible classes of scaling limits
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Bouadoumou, Maxime K. "Jackknife Empirical Likelihood for the Accelerated Failure Time Model with Censored Data." Digital Archive @ GSU, 2011. http://digitalarchive.gsu.edu/math_theses/112.

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Kendall and Gehan estimating functions are used to estimate the regression parameter in accelerated failure time (AFT) model with censored observations. The accelerated failure time model is the preferred survival analysis method because it maintains a consistent association between the covariate and the survival time. The jackknife empirical likelihood method is used because it overcomes computation difficulty by circumventing the construction of the nonlinear constraint. Jackknife empirical likelihood turns the statistic of interest into a sample mean based on jackknife pseudo-values. U-statistic approach is used to construct the confidence intervals for the regression parameter. We conduct a simulation study to compare the Wald-type procedure, the empirical likelihood, and the jackknife empirical likelihood in terms of coverage probability and average length of confidence intervals. Jackknife empirical likelihood method has a better performance and overcomes the under-coverage problem of the Wald-type method. A real data is also used to illustrate the proposed methods.
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Books on the topic "Statistic and probability"

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Srivastava, M. S. Tail probability approximations of a general statistic with application to Durbin-Watson statistic. University of Toronto, Dept. of Statistics, 1988.

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Finetti, Bruno De. Probabilità e induzione =: Induction and probability. Editrice CLUEB, 1993.

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Bedford, Stan. Statistics: Probability. Sheffield City Polytechnic, 1985.

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Probability & statistics. Prentice Hall, 1990.

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Probability & statistics. Prentice-Hall, 1990.

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Mukhopadhyay, Nitis. Probability and statistical inference. Marcel Dekker, 2000.

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C, Runger George, ed. Applied statistics and probability for engineers. 3rd ed. Wiley, 2003.

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Montgomery, Douglas C. Applied statistics and probability for engineers. John Wiley & Sons, 1994.

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C, Runger George, ed. Applied statistics and probability for engineers. 2nd ed. John Wiley Sons, 1999.

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C, Runger George, ed. Applied statistics and probability for engineers. 4th ed. Wiley, 2006.

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Book chapters on the topic "Statistic and probability"

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Belanger, Paul, and Kieran Moore. "Cloud Computing-Enabled Cluster Detection Using a Flexibly Shaped Scan Statistic for Real-Time Syndromic Surveillance." In Wiley Series in Probability and Statistics. John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781118630013.ch9.

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Kumganbayev, Murat, and Vasilij Voinov. "On a Derivation of Probability Density Functions. The PDF of Greenwood’s Statistic." In Transactions of the Tenth Prague Conference on Information Theory, Statistical Decision Functions, Random Processes. Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-010-9913-4_11.

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Krishna Sureddi, R. M., K. V. Ranga Rao, and M. Suresh Babu. "Optimal Secured Reliable Routing Paths Identification in MANET Through Intelligent Probability Statistic Model." In Lecture Notes in Electrical Engineering. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-1465-4_2.

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Walrand, Jean. "Perspective and Complements." In Probability in Electrical Engineering and Computer Science. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-49995-2_15.

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AbstractWe have explored a number of topics motivated by concrete applications. It is time to stitch together these ideas into a complete panorama. In addition, we provide some complements.Section 15.1 discusses the general question of inference: what can one deduce from observations? Section 15.2 explains the important notion of sufficient statistic: what is the relevant data in a set of observations? Section 15.3 presents the theory of Markov chains where the number of states is infinite. Section 15.4 explains the Poisson process. Section 15.5 discusses the boosting algorithm for choosing among experts. What drug should you further research; what noisy channel should one use? These are examples of multi-armed bandit problems. In such problems one faces the trade-off between exploiting known possibilities versus exploring potentially more rewarding but less well understood alternatives. Section 15.6 explains a key results for such multi-armed bandit problems. Information Theory studies the limits of communication systems: how fast can one transmit bits reliably over a noisy channel? How many bits should be transmitted to convey some information? Section 15.7 introduces some key concepts and results of Information Theory. When estimating the likelihood of errors or the reliability of some estimates, one usually has to calculate bounds on the probability that a random variable exceeds a given value. Section 15.8 discusses some useful probability bounds. Section 15.9 explains the main ideas of the theory of martingales and shows how it provides a proof of the law of large numbers.
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Sun, Yueqing, Lin Li, Zhongwei Xie, Qing Xie, Xin Li, and Guandong Xu. "Co-training an Improved Recurrent Neural Network with Probability Statistic Models for Named Entity Recognition." In Database Systems for Advanced Applications. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55699-4_33.

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Iversen, Gudmund R., and Mary Gergen. "Probability." In Statistics. Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4612-2244-6_5.

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Rees, D. G. "Probability." In Essential Statistics. Springer US, 1989. http://dx.doi.org/10.1007/978-1-4899-7260-6_5.

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O’Hagan, Anthony. "Statistical models." In Probability. Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-1211-3_9.

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Noether, Gottfried E. "Probability." In Introduction to Statistics. Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4612-0943-0_4.

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Ball, A. D., and G. D. Buckwell. "Probability." In Statistics A Level. Macmillan Education UK, 1991. http://dx.doi.org/10.1007/978-1-349-13856-2_3.

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Conference papers on the topic "Statistic and probability"

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Du, Ping, and Bo Jiang. "Reflection on the Teaching of Probability and Statistic." In Proceedings of the 2nd International Conference on Contemporary Education, Social Sciences and Ecological Studies (CESSES 2019). Atlantis Press, 2019. http://dx.doi.org/10.2991/cesses-19.2019.39.

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GUPTA, RAMESHWAR D., DEBASIS KUNDU, and ANUBHAV MANGLICK. "PROBABILITY OF CORRECT SELECTION OF GAMMA VERSUS GE OR WEIBULL VERSUS GE BASED ON LIKELIHOOD RATIO STATISTIC." In Proceedings of Statistics 2001 Canada: The 4th Conference in Applied Statistics. PUBLISHED BY IMPERIAL COLLEGE PRESS AND DISTRIBUTED BY WORLD SCIENTIFIC PUBLISHING CO., 2002. http://dx.doi.org/10.1142/9781860949531_0012.

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Liu, M., and C. Cross. "Acceptable Target Probability of Failure for Subsea Pipeline UHB Design." In ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/omae2017-61187.

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For subsea pipeline UHB design, it is essential to establish appropriate UHB load factors by undertaking a structural reliability analysis based on a target acceptable probability of failure. The current practice is to setup the acceptable probability of failure according to the best industrial practice coded in DNV OS F101 and ISO16708 but regardless of trench performance, imperfection details and inspection results. This paper is intended to discuss the relationship between the UHB failure probability for the whole pipeline and the trench performance and imperfection frequency statistics. A detailed statistic and reliability analysis is undertaken to address some disparity in the current practice. It is shown that in order to achieve a specific reliability level required for the entire pipeline, it is paramount to calibrate the target probability of failure based on the survey data. The common practice for UHB is shown un-conservative giving rise to an insufficient safety level and non-compliant OOS design. An improved approach is outlined to address the critical issues allowing for a robust OOS assessment by means of case studies.
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Yang, BaiYun. "The Features of the Statistic Counting Model for Its Application to Estimate the Probability." In 2016 4th International Conference on Management, Education, Information and Control (MEICI 2016). Atlantis Press, 2016. http://dx.doi.org/10.2991/meici-16.2016.94.

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Kirlin, R. Lynn, and Ali M. Reza. "Maximum entropy estimation of the probability density function from the histogram using order statistic constraints." In ICASSP 2013 - 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2013. http://dx.doi.org/10.1109/icassp.2013.6638899.

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Jun, Wang, Li Yushan, and Guo Zhi. "Research on statistic characteristics of the unbiased estimation of hitting probability with rectangle objective domain." In 2013 25th Chinese Control and Decision Conference (CCDC). IEEE, 2013. http://dx.doi.org/10.1109/ccdc.2013.6561325.

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Li, Ruming, Manjit S. Kang, and Guixue Wang. "Evaluation of Statistic Probability Distribution Functions: II. Chi-Squared Probability Function and the Inverse Functions of z, t, F, and Chi-Squared Distributions." In 2016 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 2016. http://dx.doi.org/10.1109/csci.2016.0236.

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Odedina, P. K., and T. J. Afullo. "Clear-Air Analysis of Fade Exceedance Probability Statistic for Microwave Line-of-Sight Link in South Africa." In IASTED Technology Conferences 2010. ACTAPRESS, 2010. http://dx.doi.org/10.2316/p.2010.705-010.

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Li, Ruming, Manjit S. Kang, and Guixue Wang. "Evaluation of Statistic Probability Distribution Functions: I. Computation of the Standard Normal z, Student's t, F, and Chi-Squared Values." In 2016 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 2016. http://dx.doi.org/10.1109/csci.2016.0238.

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Yang, Jianming, and Ping Yang. "Random Gear Dynamics Based on Path Integration Method." In ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-85944.

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Gears exhibit vibrations during operation which contain apparently random components. Due to time-varying stiffness and backlash nonlinearity, it is very hard, if not impossible, to get a closed form response of gears under combination of deterministic and random loads. This paper employs a numerical method termed as path integration to obtain the probability density of the response at discrete time instants. The random excitation is assumed to be White noise. The response of the gear is a Markovian processes under the random excitation. In order to capture the probability density evolution, discretization is applied to both space and time. The transition probability between adjacent time instants is assumed to be Gaussian and the calculation of the probability density is made on a reduced finite space. The mean and variance, which are used to construct the Gaussian distribution, are obtained through a direct numerical integration scheme with one stochastic Newmark method. Statistic linearization technique is utilized within each individual time-step to find a linear equivalent of the original system with backlash nonlinearity. Through this method the evolution of the probability distribution function of the response displacement and the velocity is calculated. Three representative cases with different levels of constant load are investigated.
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Reports on the topic "Statistic and probability"

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Sethuraman, Jayaram. Problems in Probability, Statistics and Reliability. Defense Technical Information Center, 1996. http://dx.doi.org/10.21236/ada316857.

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Yost, G. P. Lectures on probability and statistics. Revision. Office of Scientific and Technical Information (OSTI), 1985. http://dx.doi.org/10.2172/5436995.

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Sethuraman, Jayaram. Problems in Reliability, Statistics and Probability. Defense Technical Information Center, 1986. http://dx.doi.org/10.21236/ada171447.

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Sethuraman, Jayaram. Problems in Probability, Statistics and Reliability. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada270830.

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Sethuraman, Jayaram. Problems in Probability, Statistics and Reliability. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada224152.

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Sethuraman, Jayaram. Some Problems in Probability, Statistics and Reliability. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada392537.

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Chung, C. F. Working group 4 - Probability and statistics in geoscience. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1990. http://dx.doi.org/10.4095/222365.

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Steele, J. M. Probability and Statistics Applied to the Theory of Algorithms. Defense Technical Information Center, 1995. http://dx.doi.org/10.21236/ada295805.

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SOHN, HOON, DAVID W. ALLEN, KEITH WORDEN, and CHARLES R. FARRAR. STATISTICAL DAMAGE CLASSIFICATION USING SEQUENTIAL PROBABILITY RATIO TESTS. Office of Scientific and Technical Information (OSTI), 2002. http://dx.doi.org/10.2172/808089.

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Marcu, Daniel, and William Wong. A Phrase-Based, Joint Probability for Statistical Machine Translation. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada461277.

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