Relevant bibliographies by topics / Normal models

Contents

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

Academic literature on the topic 'Normal models'

Author: Grafiati
Published: 4 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Normal models"

1

Martinec, Zedeněk, Karel Pěč, and M. Burša. "Normal density earth models." Studia Geophysica et Geodaetica 30, no. 2 (1986): 124–47. http://dx.doi.org/10.1007/bf01644373.

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Bernstein, Daniel Irving, and Seth Sullivant. "Normal Binary Hierarchical Models." Experimental Mathematics 26, no. 2 (2016): 153–64. http://dx.doi.org/10.1080/10586458.2016.1142911.

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Sullivant, Seth. "Normal binary graph models." Annals of the Institute of Statistical Mathematics 62, no. 4 (2010): 717–26. http://dx.doi.org/10.1007/s10463-010-0296-3.

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Arellano-Valle, R. B., H. Bolfarine, and V. H. Lachos. "Skew-normal Linear Mixed Models." Journal of Data Science 3, no. 4 (2021): 415–38. http://dx.doi.org/10.6339/jds.2005.03(4).238.

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Urbinati, Stefano. "Divisorial Models of Normal Varieties." Proceedings of the Edinburgh Mathematical Society 60, no. 4 (2017): 1053–64. http://dx.doi.org/10.1017/s0013091516000614.

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AbstractWe prove that the canonical ring of a canonical variety in the sense of de Fernex and Hacon is finitely generated. We prove that canonical varieties are Kawamata log terminal (klt) if and only if is finitely generated. We introduce a notion of nefness for non-ℚ-Gorenstein varieties and study some of its properties. We then focus on these properties for non-ℚ-Gorenstein toric varieties.
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Arellano-Valle, R. B., S. Ozan, H. Bolfarine, and V. H. Lachos. "Skew normal measurement error models." Journal of Multivariate Analysis 96, no. 2 (2005): 265–81. http://dx.doi.org/10.1016/j.jmva.2004.11.002.

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Krasiński, Andrzej. "Shear‐free normal cosmological models." Journal of Mathematical Physics 30, no. 2 (1989): 433–41. http://dx.doi.org/10.1063/1.528462.

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Kato, Kazuya, Chikara Nakayama, and Sampei Usui. "Néron models for admissible normal functions." Proceedings of the Japan Academy, Series A, Mathematical Sciences 90, no. 1 (2014): 6–10. http://dx.doi.org/10.3792/pjaa.90.6.

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Martínez-Flórez, Guillermo, Diego I. Gallardo, Osvaldo Venegas, Heleno Bolfarine, and Héctor W. Gómez. "Flexible Power-Normal Models with Applications." Mathematics 9, no. 24 (2021): 3183. http://dx.doi.org/10.3390/math9243183.

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The main object of this paper is to propose a new asymmetric model more flexible than the generalized Gaussian model. The probability density function of the new model can assume bimodal or unimodal shapes, and one of the parameters controls the skewness of the model. Three simulation studies are reported and two real data applications illustrate the flexibility of the model compared with traditional proposals in the literature.
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Miyaoka, Etsuo. "Estimation in Logistic Normal Linear Models." Japanese Journal of Biometrics 12 (1991): 99–104. http://dx.doi.org/10.5691/jjb.12.99.

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Dissertations / Theses on the topic "Normal models"

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Frühwirth-Schnatter, Sylvia. "Recursive Residuals and Model Diagnostics for Normal and Non-Normal State Space Models." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 1994. http://epub.wu.ac.at/1540/1/document.pdf.

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Model diagnostics for normal and non-normal state space models is based on recursive residuals which are defined from the one-step ahead predictive distribution. Routine calculation of these residuals is discussed in detail. Various tools of diagnostics are suggested to check e.g. for wrong observation distributions and for autocorrelation. The paper also covers such topics as model diagnostics for discrete time series, model diagnostics for generalized linear models, and model discrimination via Bayes factors. (author's abstract)<br>Series: Forschungsberichte / Institut für Statistik
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Al-Bashabsheh, Ali. "Normal Factor Graphs." Thèse, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/30659.

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This thesis introduces normal factor graphs under a new semantics, namely, the exterior function semantics. Initially, this work was motivated by two distinct lines of research. One line is ``holographic algorithms,'' a powerful approach introduced by Valiant for solving various counting problems in computer science; the other is ``normal graphs,'' an elegant framework proposed by Forney for representing codes defined on graphs. The nonrestrictive normality constraint enables the notion of holographic transformations for normal factor graphs. We establish a theorem, called the generalized Ho
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Vinerean, Mirela Christina. "Classification of Normal Discrete Kinetic Models." Licentiate thesis, Karlstad University, Division for Engineering Sciences, Physics and Mathematics, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-2431.

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<p>“In many interesting papers on discrete velocity models (DVMs), authors postulate from the beginning that the finite velocity space with "good" properties is given and only after this step they study the Discrete Boltzmann Equation. Contrary to this approach, our aim is not to study the equation, but to discuss all possible choices of finite phase spaces (sets) satisfying this type of "good" restrictions. Due to the velocity discretization it is well known that it is possible to have DVMs with "spurious" summational invariants (conservation laws which are not linear combinations of physical
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Panda, Manasa Ranjan. "Computer models of normal and impaired hearing." Thesis, University of Exeter, 2010. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.528857.

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Shen, Yichang. "Reduced-order models for geometrically nonlinear vibrations of thin structures." Thesis, Institut polytechnique de Paris, 2021. http://www.theses.fr/2021IPPAE012.

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Lorsqu'elles vibrent avec de grandes amplitudes, les structures minces montrent un comportement non linéaire géométrique, provenant de la relation non linéaire entre les déformations et les déplacements. Les analyses des systèmes complets font appel à des calculs extrêmement couteux de telle sorte que l'établissement de modèles d'ordre réduit efficaces est un sujet d'intérêt majeur pour le calcul prédictif de vibrations de structures minces.Dans cette thèse, des méthodes non linéaires de réduction de modèle pour les structures discrétisées par la méthode des éléments finis et comportant une no
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Roux, Hannaline. "Construction and parameter estimation of wrapped normal models." Diss., University of Pretoria, 2019. http://hdl.handle.net/2263/77880.

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If a known distribution on a real line is given, it can be wrapped on the circumference of a unit circle. This research entails the study of a univariate skew-normal distribution where the skew-normal distribution is generalised for the case of bimodality. Both the skew-normal and exible generalised skew-normal distributions are wrapped onto a unit circle, consequently referred to as a wrapped skew-normal and a wrapped exible generalised skew-normal distribution respectively. For each of these distributions a simulation study is conducted, where the performance of maximum likelihood
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Frühwirth-Schnatter, Sylvia. "Bayesian Model Discrimination and Bayes Factors for Normal Linear State Space Models." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 1993. http://epub.wu.ac.at/108/1/document.pdf.

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It is suggested to discriminate between different state space models for a given time series by means of a Bayesian approach which chooses the model that minimizes the expected loss. Practical implementation of this procedures requires a fully Bayesian analysis for both the state vector and the unknown hyperparameters which is carried out by Markov chain Monte Carlo methods. Application to some non-standard situations such as testing hypotheses on the boundary of the parameter space, discriminating non-nested models and discrimination of more than two models is discussed in detail. (author's a
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Devamitta, Perera Muditha Virangika. "Robustness of normal theory inference when random effects are not normally distributed." Kansas State University, 2011. http://hdl.handle.net/2097/8786.

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Master of Science<br>Department of Statistics<br>Paul I. Nelson<br>The variance of a response in a one-way random effects model can be expressed as the sum of the variability among and within treatment levels. Conventional methods of statistical analysis for these models are based on the assumption of normality of both sources of variation. Since this assumption is not always satisfied and can be difficult to check, it is important to explore the performance of normal based inference when normality does not hold. This report uses simulation to explore and assess the robustness of the F-test fo
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Qi, Meng. "Development in Normal Mixture and Mixture of Experts Modeling." UKnowledge, 2016. http://uknowledge.uky.edu/statistics_etds/15.

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In this dissertation, first we consider the problem of testing homogeneity and order in a contaminated normal model, when the data is correlated under some known covariance structure. To address this problem, we developed a moment based homogeneity and order test, and design weights for test statistics to increase power for homogeneity test. We applied our test to microarray about Down’s syndrome. This dissertation also studies a singular Bayesian information criterion (sBIC) for a bivariate hierarchical mixture model with varying weights, and develops a new data dependent information criterio
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Chang, Ilsung. "Bayesian inference on mixture models and their applications." Texas A&M University, 2003. http://hdl.handle.net/1969.1/3990.

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Mixture models are useful in describing a wide variety of random phenomena because of their flexibility in modeling. They have continued to receive increasing attention over the years from both a practical and theoretical point of view. In their applications, estimating the number of mixture components is often the main research objective or the first step toward it. Estimation of the number of mixture components heavily depends on the underlying distribution. As an extension of normal mixture models, we introduce a skew-normal mixture model and adapt the reversible jump Markov chain Monte Car
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Books on the topic "Normal models"

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Wim J. van der Linden. Normal models for response times on test items. Law School Admission Council, 2006.

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Rosen, Dietrich von. Multivariate linear normal models with special references to the growth curve model. Stockholms Universitet, 1985.

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Clark, Todd E. Approximately normal tests for equal predictive accuracy in nested models. Research Division, Federal Reserve Bank of Kansas City, 2005.

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H, Andersen H., ed. Linear and graphical models: For the multivariate complex normal distribution. Springer-Verlag, 1995.

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Baggett, Jeffrey S. Non-normal dynamics and hydrodynamic stability. Cornell Theory Center, Cornell University, 1996.

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Fleet, David J. Computation of normal velocity from local phase information. University of Toronto, Dept. of Computer Science, 1989.

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Dewald, Lee Samuel. Times series models with a specified symmetric non-normal marginal distribution. Naval Postgraduate School, 1985.

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Montfort, Kees van. Estimating in structural models with non-normal distributed variables: some alternative approaches. DSWO Press, 1988.

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Dueker, Michael. Kalman filtering with truncated normal state variables for Bayesian estimation of macroeconomic models. Federal Reserve Bank of St. Louis, 2005.

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Skip, Morrow, and Goddard Space Flight Center, eds. Normal modes of the world's oceans: A numerical investigation using Proudman functions. National Aeronautics and Space Administration, Goddard Space Flight Center, 1993.

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Book chapters on the topic "Normal models"

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Hooten, Mevin B., and Trevor J. Hefley. "Normal-Normal." In Bringing Bayesian Models to Life. CRC Press, 2019. http://dx.doi.org/10.1201/9780429243653-7.

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Marin, Jean-Michel, and Christian P. Robert. "Normal Models." In Springer Texts in Statistics. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8687-9_2.

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Hooten, Mevin B., and Trevor J. Hefley. "Normal-Normal-Inverse Gamma." In Bringing Bayesian Models to Life. CRC Press, 2019. http://dx.doi.org/10.1201/9780429243653-9.

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Brinda, W. D. "Normal Errors." In Visualizing Linear Models. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-64167-2_6.

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Kalbfleisch, J. G. "Normal Linear Models." In Springer Texts in Statistics. Springer New York, 1985. http://dx.doi.org/10.1007/978-1-4612-5136-1_6.

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Lauritzen, Steffen. "Linear Normal Models." In Fundamentals of Mathematical Statistics. Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003272359-2.

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Zwanzig, Silvelyn, and Rauf Ahmad. "Normal Linear Models." In Bayesian Inference. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003221623-6.

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Byun, Sung-Soo, and Peter J. Forrester. "Normal Matrix Models." In KIAS Springer Series in Mathematics. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-5173-0_5.

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AbstractNormal matrix models, characterised by the requirement that the matrices commute with their adjoint so that their eigenvectors form a unitary matrix, permit an explicit Coulomb gas Boltzmann factor type eigenvalue PDF with $$\beta =2$$ β = 2 , so determinantal structures hold. They permit a simplified global scaling in which the one-body potential is taken as being strictly proportional to N. The support of the corresponding large N equilibrium measure is referred to as a droplet. Perturbing the GinUE one-body potential by the real part of a polynomial leads to a relation between the m
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Blumenthal, George R. "Models of Protogalaxy Collapse and Dissipation." In Nearly Normal Galaxies. Springer New York, 1987. http://dx.doi.org/10.1007/978-1-4612-4762-3_45.

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Andersen, H. H., M. Højbjerre, D. Sørensen, and P. S. Eriksen. "Complex Normal Graphical Models." In Linear and Graphical Models. Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4612-4240-6_7.

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Conference papers on the topic "Normal models"

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Gstöttner, Conrad, Bernd Kolar, and Markus Schöberl. "A Triangular Normal Form for x-Flat Control-Affine Two-Input Systems." In 2024 28th International Conference on Methods and Models in Automation and Robotics (MMAR). IEEE, 2024. http://dx.doi.org/10.1109/mmar62187.2024.10680807.

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Ma, Wan, Shanfei Shi, Chuang Zhu, Beiyuan Xing, Yaping Wang, and Jiangbo Shu. "Exploration of AI-Empowered Professional Skill Training Models for Normal School Students." In 2024 4th International Conference on Educational Technology (ICET). IEEE, 2024. https://doi.org/10.1109/icet62460.2024.10868158.

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Petngam, Pat, Songpol Ongwattanakul, Thunyanoot Prasertsakul, and Warakorn Charoensuk. "Estimation of Human Postural Models Using Artificial Neural Networks Under Normal and Overweight Conditions." In 2024 16th Biomedical Engineering International Conference (BMEiCON). IEEE, 2024. https://doi.org/10.1109/bmeicon64021.2024.10896297.

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Ramesh, Nisha, Fitsum Mesadi, Mujdat Cetin, and Tolga Tasdizen. "Disjunctive normal shape models." In 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI 2015). IEEE, 2015. http://dx.doi.org/10.1109/isbi.2015.7164170.

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Merry, Bruce, Patrick Marais, and James Gain. "Normal transformations for articulated models." In ACM SIGGRAPH 2006 Sketches. ACM Press, 2006. http://dx.doi.org/10.1145/1179849.1180017.

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Stein, David W. J. "Normal compositional models: generalizations and applications." In AeroSense 2002, edited by Sylvia S. Shen and Paul E. Lewis. SPIE, 2002. http://dx.doi.org/10.1117/12.478753.

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Kokonendji, Célestin C., and Khoirin Nisa. "Generalized Variance Estimations of Normal Poisson Models." In Annual International Conference on Computational Mathematics, Computational Geometry & Statistics (CMCGS 2014). GSTF, 2014. http://dx.doi.org/10.5176/2251-1911_cmcgs14.29.

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Bobylev, A. V., and M. C. Vinerean. "Symmetric extensions of normal discrete velocity models." In 28TH INTERNATIONAL SYMPOSIUM ON RAREFIED GAS DYNAMICS 2012. AIP, 2012. http://dx.doi.org/10.1063/1.4769516.

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Fonseca, Miguel, Thomas Mathew, João T. Mexia, et al. "Confidence Intervals for Mixed Log-Normal Models." In NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2011: International Conference on Numerical Analysis and Applied Mathematics. AIP, 2011. http://dx.doi.org/10.1063/1.3636919.

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Inoue, Akio K. "Attenuation law of normal disk galaxies." In THE SPECTRAL ENERGY DISTRIBUTIONS OF GAS-RICH GALAXIES: Confronting Models with Data; International Workshop. AIP, 2005. http://dx.doi.org/10.1063/1.1913942.

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Reports on the topic "Normal models"

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Eslinger, Paul W., and Wayne A. Woodward. Minimum Hellinger Distance Estimation for Normal Models. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada228714.

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West, Kenneth, and Todd Clark. Approximately Normal Tests for Equal Predictive Accuracy in Nested Models. National Bureau of Economic Research, 2006. http://dx.doi.org/10.3386/t0326.

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Amengual, Dante, Xinyue Bei, Marine Carrasco, and Enrique Sentana. Score-type tests for normal mixtures. CIRANO, 2023. http://dx.doi.org/10.54932/uxsg1990.

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Testing normality against discrete normal mixtures is complex because some parameters turn increasingly underidentified along alternative ways of approaching the null, others are inequality constrained, and several higher-order derivatives become identically 0. These problems make the maximum of the alternative model log-likelihood function numerically unreliable. We propose score-type tests asymptotically equivalent to the likelihood ratio as the largest of two simple intuitive statistics that only require estimation under the null. One novelty of our approach is that we treat symmetrically b
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Gelfand, Alan E., Susan E. Hills, Amy Racine-Poon, and Adrian F. Smith. Illustration of Bayesian Inference in Normal Data Models Using Gibbs Sampling. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada212630.

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Nielson, Gregory M. Normalized Implicit Radial Models for Scattered Point Cloud Data without Normal Vectors. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada499959.

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Dueker, Michael J. Kalman Filtering with Truncated Normal State Variables for Bayesian Estimation of Macroeconomic Models. Federal Reserve Bank of St. Louis, 2005. http://dx.doi.org/10.20955/wp.2005.057.

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Balk, Ethan, Elyse Couch, Htun Ja Mai, et al. Fiber Intake and Laxation in People With Normal Bowel Function. AHRQ, 2025. https://doi.org/10.23970/ahrqepcsrlaxation.

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Objectives. To support a planned update of the Dietary Recommended Intake of macronutrients, including dietary fiber, we conducted a systematic review of the effect of fiber on laxation outcomes (related to gut motility) in people with normal bowel function. Data sources and review methods. We searched PubMed, Embase, and existing systematic reviews to March 4, 2025 for randomized trials in the general population of people in any life stage (without bowel dysfunction) that compared amounts, types, or forms of fiber. Outcomes of interest were stool consistency, fecal weight, fecal frequency, gu
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Zhao, Haihua, Ling Zou, Hongbin Zhang, and James Edward O'Brien. Development and Implementation of Mechanistic Terry Turbine Models in RELAP-7 to Simulate RCIC Normal Operation Conditions. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1364523.

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Bodie, Mark, Michael Parker, Alexander Stott, and Bruce Elder. Snow-covered obstacles’ effect on vehicle mobility. Engineer Research and Development Center (U.S.), 2020. http://dx.doi.org/10.21079/11681/38839.

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The Mobility in Complex Environments project used unmanned aerial systems (UAS) to identify obstacles and to provide path planning in forward operational locations. The UAS were equipped with remote-sensing devices, such as photogrammetry and lidar, to identify obstacles. The path-planning algorithms incorporated the detected obstacles to then identify the fastest and safest vehicle routes. Future algorithms should incorporate vehicle characteristics as each type of vehicle will perform differently over a given obstacle, resulting in distinctive optimal paths. This study explored the effect of
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Otrok, Christopher, Huigang Chen, Alessandro Rebucci, Gianluca Benigno, and Eric R. Young. Revisiting Overborrowing and Its Policy Implications. Inter-American Development Bank, 2010. http://dx.doi.org/10.18235/0010985.

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This paper analyzes quantitatively the extent to which there is overborrowing (i.e., inefficient borrowing) in a business cycle model for emerging market economies with production and an occasionally binding credit constraint. The main finding of the analysis is that overborrowing is not a robust feature of this class of model economies: it depends on the structure of the economy and its parametrization. Specifcally, underborrowing in a production economy is found with the baseline calibration, but overborrowing with more impatient agents and more volatile shocks. Endowment economies display o
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