Relevant bibliographies by topics / Gauss Markov model with constraints

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Academic literature on the topic 'Gauss Markov model with constraints'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 February 2022

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Journal articles on the topic "Gauss Markov model with constraints"

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Larocca, Roger. "Reconciling Conflicting Gauss-Markov Conditions in the Classical Linear Regression Model." Political Analysis 13, no. 2 (2005): 188–207. http://dx.doi.org/10.1093/pan/mpi011.

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This article reconciles conflicting accounts of Gauss-Markov conditions, which specify when ordinary least squares (OLS) estimators are also best linear unbiased (BLU) estimators. We show that exogeneity constraints that are commonly assumed in econometric treatments of the Gauss-Markov theorem are unnecessary for OLS estimates of the classical linear regression model to be BLU. We also generalize a set of necessary and sufficient conditions first established by McElroy (1967, Journal of the American Statistical Association 62:1302–1304), but not yet generally recognized in the econometric lit
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Schaffrin, Burkhard, and Gerhard Navratil. "On Reproducing Linear Estimators within the Gauss–Markov Model with Stochastic Constraints." Communications in Statistics - Theory and Methods 41, no. 13-14 (2012): 2570–87. http://dx.doi.org/10.1080/03610926.2011.631073.

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Sluis, B., and C. Toth. "2-DIMENSIONAL GEOMETRIC ANALYSIS OF A SIMPLE FREE NETWORK." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-4-2021 (June 17, 2021): 147–52. http://dx.doi.org/10.5194/isprs-annals-v-4-2021-147-2021.

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Abstract. This paper attempts to quantify geometric considerations in observations and observe trends in solutions to free network solutions. The method of investigation will be utilizing 2D observations to determine how each measurement affects the overall solution and the location of the observations relative to the other nodes. A local reference system will be determined using the Gauss-Markov model with constraints by fixing the largest range observation to the y-axis to give a relative orientation. Further solutions will be calculated by fixing additional points to generate multiple least
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Chen, Jinsong, Andreas Kemna, and Susan S. Hubbard. "A comparison between Gauss-Newton and Markov-chain Monte Carlo–based methods for inverting spectral induced-polarization data for Cole-Cole parameters." GEOPHYSICS 73, no. 6 (2008): F247—F259. http://dx.doi.org/10.1190/1.2976115.

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We have developed a Bayesian model to invert spectral induced-polarization (SIP) data for Cole-Cole parameters using Markov-chain Monte Carlo (MCMC) sampling methods. We compared the performance of the MCMC-based stochastic method with an iterative Gauss-Newton-based deterministic method for Cole-Cole parameter estimation through inversion of synthetic and laboratory SIP data. The Gauss-Newton-based method can provide an optimal solution for given objective functions under constraints, but the obtained optimal solution generally depends on the choice of initial values and the estimated uncerta
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Prószyński, Witold. "Investigating the links of internal and external reliability with the system conditionality in Gauss-Markov models with uncorrelated observations." Geodesy and Cartography 62, no. 2 (2013): 157–81. http://dx.doi.org/10.2478/geocart-2013-0010.

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Abstract The relationship between internal response-based reliability and conditionality is investigated for Gauss-Markov (GM) models with uncorrelated observations. The models with design matrices of full rank and of incomplete rank are taken into consideration. The formulas based on the Singular Value Decomposition (SVD) of the design matrix are derived which clearly indicate that the investigated concepts are independent of each other. The methods are presented of constructing for a given design matrix the matrices equivalent with respect to internal response-based reliability as well as th
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Dehbi, Y., J. H. Haunert, and L. Plümer. "STOCHASTIC AND GEOMETRIC REASONING FOR INDOOR BUILDING MODELS WITH ELECTRIC INSTALLATIONS – BRIDGING THE GAP BETWEEN GIS AND BIM." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-4/W5 (October 23, 2017): 33–39. http://dx.doi.org/10.5194/isprs-annals-iv-4-w5-33-2017.

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3D city and building models according to CityGML encode the geometry, represent the structure and model semantically relevant building parts such as doors, windows and balconies. Building information models support the building design, construction and the facility management. In contrast to CityGML, they include also objects which cannot be observed from the outside. The three dimensional indoor models characterize a missing link between both worlds. Their derivation, however, is expensive. The semantic automatic interpretation of 3D point clouds of indoor environments is a methodically deman
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Werner, H. J., and C. Yapar. "On inequality constrained generalized least squares selections in the general possibly singular Gauss-Markov model: A projector theoretical approach." Linear Algebra and its Applications 237-238 (April 1996): 359–93. http://dx.doi.org/10.1016/0024-3795(94)00357-2.

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Omidalizarandi, Mohammad, Boris Kargoll, Jens-André Paffenholz, and Ingo Neumann. "Robust external calibration of terrestrial laser scanner and digital camera for structural monitoring." Journal of Applied Geodesy 13, no. 2 (2019): 105–34. http://dx.doi.org/10.1515/jag-2018-0038.

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Abstract In the last two decades, the integration of a terrestrial laser scanner (TLS) and digital photogrammetry, besides other sensors integration, has received considerable attention for deformation monitoring of natural or man-made structures. Typically, a TLS is used for an area-based deformation analysis. A high-resolution digital camera may be attached on top of the TLS to increase the accuracy and completeness of deformation analysis by optimally combining points or line features extracted both from three-dimensional (3D) point clouds and captured images at different epochs of time. Fo
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Alenazi, Mohammed J. F., Shatha O. Abbas, Saleh Almowuena, and Maazen Alsabaan. "RSSGM: Recurrent Self-Similar Gauss–Markov Mobility Model." Electronics 9, no. 12 (2020): 2089. http://dx.doi.org/10.3390/electronics9122089.

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Understanding node mobility is critical for the proper simulation of mobile devices in a wireless network. However, current mobility models often do not reflect the realistic movements of users within their environments. They also do not provide the freedom to adjust their degrees of randomness or adequately mimic human movements by injecting possible crossing points and adding recurrent patterns. In this paper, we propose the recurrent self-similar Gauss–Markov mobility (RSSGM) model, a novel mobility model that is suitable for applications in which nodes exhibit recurrent visits to selected
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Jun Zhang. "Parameter reduction for the compound Gauss-Markov model." IEEE Transactions on Image Processing 4, no. 3 (1995): 382–86. http://dx.doi.org/10.1109/83.366485.

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Dissertations / Theses on the topic "Gauss Markov model with constraints"

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Cothren, Jackson D. "Reliability in constrained Gauss-Markov models an analytical and differential approach with applications in photogrammetry /." Connect to this title online, 2004. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1085689960.

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Thesis (Ph. D.)--Ohio State University, 2004.<br>Title from first page of PDF file. Document formatted into pages; contains xii, 119 p.; also includes graphics (some col.). Includes bibliographical references (p. 106-109). Available online via OhioLINK's ETD Center
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Lehmann, Rüdiger, and Frank Neitzel. "Testing the compatibility of constraints for parameters of a geodetic adjustment model." Hochschule für Technik und Wirtschaft Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:520-qucosa-148609.

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Geodetic adjustment models are often set up in a way that the model parameters need to fulfil certain constraints. The normalized Lagrange multipliers have been used as a measure of the strength of constraint in such a way that if one of them exceeds in magnitude a certain threshold then the corresponding constraint is likely to be incompatible with the observations and the rest of the constraints. We show that these and similar measures can be deduced as test statistics of a likelihood ratio test of the statistical hypothesis that some constraints are incompatible in the same sense. This has
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Lehmann, Rüdiger, and Frank Neitzel. "Testing the compatibility of constraints for parameters of a geodetic adjustment model." Springer Verlag, 2013. https://htw-dresden.qucosa.de/id/qucosa%3A23273.

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Geodetic adjustment models are often set up in a way that the model parameters need to fulfil certain constraints. The normalized Lagrange multipliers have been used as a measure of the strength of constraint in such a way that if one of them exceeds in magnitude a certain threshold then the corresponding constraint is likely to be incompatible with the observations and the rest of the constraints. We show that these and similar measures can be deduced as test statistics of a likelihood ratio test of the statistical hypothesis that some constraints are incompatible in the same sense. This has
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Lehmann, Rüdiger. "Transformation model selection by multiple hypotheses testing." Hochschule für Technik und Wirtschaft Dresden, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:520-qucosa-211719.

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Transformations between different geodetic reference frames are often performed such that first the transformation parameters are determined from control points. If in the first place we do not know which of the numerous transformation models is appropriate then we can set up a multiple hypotheses test. The paper extends the common method of testing transformation parameters for significance, to the case that also constraints for such parameters are tested. This provides more flexibility when setting up such a test. One can formulate a general model with a maximum number of transformation para
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Lehmann, Rüdiger. "Transformation model selection by multiple hypotheses testing." Hochschule für Technik und Wirtschaft Dresden, 2014. https://htw-dresden.qucosa.de/id/qucosa%3A23299.

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Transformations between different geodetic reference frames are often performed such that first the transformation parameters are determined from control points. If in the first place we do not know which of the numerous transformation models is appropriate then we can set up a multiple hypotheses test. The paper extends the common method of testing transformation parameters for significance, to the case that also constraints for such parameters are tested. This provides more flexibility when setting up such a test. One can formulate a general model with a maximum number of transformation para
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Alenazi, Mohammed J. F., and Cenk Sahin. "Design Improvement and Implementation of 3D Gauss-Markov Mobility Model." International Foundation for Telemetering, 2012. http://hdl.handle.net/10150/581657.

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ITC/USA 2012 Conference Proceedings / The Forty-Eighth Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2012 / Town and Country Resort & Convention Center, San Diego, California<br>The current ns-3 implementation of the 3D Gauss-Markov mobility model (3D-GMMM) allows mobile nodes to reach and bounce off the simulation boundaries. This causes sudden and unnatural movement of the nodes in the vicinity of the simulation boundaries. In this paper, we present a modification to the current ns-3 implementation of the 3D-GMMM. We follow an approach in which mobile
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Kargoll, Boris. "On the theory and application of model misspecification tests in geodesy /." Bonn : Igg, 2008. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=016737999&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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Broyles, Dan, and Abdul Jabbar. "Design and Analysis of a 3-D Gauss-Markov Model for Highly Dynamic Airborne Networks." International Foundation for Telemetering, 2010. http://hdl.handle.net/10150/604297.

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ITC/USA 2010 Conference Proceedings / The Forty-Sixth Annual International Telemetering Conference and Technical Exhibition / October 25-28, 2010 / Town and Country Resort & Convention Center, San Diego, California<br>Accurate mobility models are needed to simulate the physical movement of nodes in a highly-dynamic aeronautical network. The fundamental problem with many synthetic mobility models is their random, memoryless behavior. Airborne ad hoc networks require a flexible memory-based 3-dimensional mobility model. We present a new 3-dimensional implementation of the Gauss-Markov mobility m
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Lehmann, Rüdiger. "Improved critical values for extreme normalized and studentized residuals in Gauss-Markov models." Hochschule für Technik und Wirtschaft Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:520-qucosa-148651.

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We investigate extreme studentized and normalized residuals as test statistics for outlier detection in the Gauss-Markov model possibly not of full rank. We show how critical values (quantile values) of such test statistics are derived from the probability distribution of a single studentized or normalized residual by dividing the level of error probability by the number of residuals. This derivation neglects dependencies between the residuals. We suggest improving this by a procedure based on the Monte Carlo method for the numerical computation of such critical values up to arbitrary precisio
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Lehmann, Rüdiger. "Improved critical values for extreme normalized and studentized residuals in Gauss-Markov models." Springer Verlag, 2012. https://htw-dresden.qucosa.de/id/qucosa%3A23275.

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We investigate extreme studentized and normalized residuals as test statistics for outlier detection in the Gauss-Markov model possibly not of full rank. We show how critical values (quantile values) of such test statistics are derived from the probability distribution of a single studentized or normalized residual by dividing the level of error probability by the number of residuals. This derivation neglects dependencies between the residuals. We suggest improving this by a procedure based on the Monte Carlo method for the numerical computation of such critical values up to arbitrary precisio
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Books on the topic "Gauss Markov model with constraints"

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Basu, Sanjay. Practicing Techniques in Context. Edited by Sanjay Basu. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190667924.003.0006.

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Four major types of modeling were detailed in the preceding chapters. (1) The problem of resource allocation, which was extended to deal with the allocation of multiple resources in the context of multiple constraints. (2) Value of information problems, which ask how much should be paid to get more information to help with decision-making. (3) Queuing problems, which ask how to minimize waiting times for a service when demand is higher than supply. And (4), extending the simple “one-box” queuing model to a multibox Markov model, which determines how to estimate the incidence and prevalence of
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Book chapters on the topic "Gauss Markov model with constraints"

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Lichters, Roland, Roland Stamm, and Donal Gallagher. "Linear Gauss Markov Model." In Modern Derivatives Pricing and Credit Exposure Analysis. Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137494849_30.

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Zimmerman, Dale L. "Least Squares Estimation for the Gauss–Markov Model." In Linear Model Theory. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52063-2_7.

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Zimmerman, Dale L. "Least Squares Estimation for the Gauss–Markov Model." In Linear Model Theory. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52074-8_7.

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Kłaczyński, K., and P. Pordzik. "On Improving Estimation in a Restricted Gauss-Markov Model." In Linear Statistical Inference. Springer New York, 1985. http://dx.doi.org/10.1007/978-1-4615-7353-1_13.

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Nordström, K. "On a Decomposition of the Singular Gauss-Markov Model." In Linear Statistical Inference. Springer New York, 1985. http://dx.doi.org/10.1007/978-1-4615-7353-1_19.

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Christensen, Ronald. "Estimation and Testing in a General Gauss-Markov Model." In Springer Texts in Statistics. Springer New York, 1987. http://dx.doi.org/10.1007/978-1-4757-1951-2_10.

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Zontek, S. "Characterization of Linear Admissible Estimators in Gauss-Markov Model under Normality." In Linear Statistical Inference. Springer New York, 1985. http://dx.doi.org/10.1007/978-1-4615-7353-1_22.

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Grau-Moya, Jordi, Felix Leibfried, Tim Genewein, and Daniel A. Braun. "Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes." In Machine Learning and Knowledge Discovery in Databases. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46227-1_30.

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Backenköhler, Michael, Luca Bortolussi, Gerrit Großmann, and Verena Wolf. "Analysis of Markov Jump Processes under Terminal Constraints." In Tools and Algorithms for the Construction and Analysis of Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72016-2_12.

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AbstractMany probabilistic inference problems such as stochastic filtering or the computation of rare event probabilities require model analysis under initial and terminal constraints. We propose a solution to this bridging problem for the widely used class of population-structured Markov jump processes. The method is based on a state-space lumping scheme that aggregates states in a grid structure. The resulting approximate bridging distribution is used to iteratively refine relevant and truncate irrelevant parts of the state-space. This way, the algorithm learns a well-justified finite-state projection yielding guaranteed lower bounds for the system behavior under endpoint constraints. We demonstrate the method’s applicability to a wide range of problems such as Bayesian inference and the analysis of rare events.
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"Gauss–Markov Model." In A Primer on Linear Models. Chapman and Hall/CRC, 2008. http://dx.doi.org/10.1201/b11551-6.

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Conference papers on the topic "Gauss Markov model with constraints"

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Brailean, James C., and Aggelos K. Katsaggelos. "Displacement field estimation using a coupled Gauss-Markov model." In Optical Engineering Midwest 1992, edited by Robert J. Heaston. SPIE, 1992. http://dx.doi.org/10.1117/12.130976.

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Papila, I., and B. Yazgan. "Hidden Gauss Markov model for multiscale remotely sensed image segmentation." In Proceedings of International Conference on Recent Advances in Space Technologies. IEEE, 2003. http://dx.doi.org/10.1109/rast.2003.1303934.

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Sun, Ning, Taebo Shim, and Hernsoo Hahn. "Sonar Image Segmentation Based on Markov Gauss-Rayleigh Mixture Model." In 2008 International Workshop on Geoscience and Remote Sensing (ETT and GRS). IEEE, 2008. http://dx.doi.org/10.1109/ettandgrs.2008.380.

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Wang, Li-jing, Kun Gao, Xin-man Cheng, Meng Wang, and Xiang-hu Miu. "A Hyperspectral Imagery Anomaly Detection Algorithm Based on Gauss-Markov Model." In 2012 Fourth International Conference on Computational and Information Sciences (ICCIS). IEEE, 2012. http://dx.doi.org/10.1109/iccis.2012.21.

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Werner, Hans Joachim. "On the Linear Aggregation Problem in the General Gauss-Markov Model." In Proceedings of the International Statistics Workshop. WORLD SCIENTIFIC, 2006. http://dx.doi.org/10.1142/9789812772466_0027.

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Photios Stavrou, A., Jan Ostergaard, and Mikael Skoglund. "On Zero-delay Source Coding of LTI Gauss-Markov Systems with Covariance Matrix Distortion Constraints." In 2018 17th European Control Conference (ECC). IEEE, 2018. http://dx.doi.org/10.23919/ecc.2018.8550204.

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Minwei Jiang. "Matrix parameterization method for solving Ill-conditioned Problem of Gauss-Markov model." In 2010 International Conference on Computer Application and System Modeling (ICCASM 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccasm.2010.5620324.

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Jiang, Minwei. "Multi-step Method for Resolving Ill-conditioned Problem of Gauss-markov Model." In 2nd International Conference on Computer Application and System Modeling. Atlantis Press, 2012. http://dx.doi.org/10.2991/iccasm.2012.312.

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Rohrer, Justin P., Egemen K. Cetinkaya, Hemanth Narra, Dan Broyles, Kevin Peters, and James P. G. Sterbenz. "AeroRP performance in highly-dynamic airborne networks using 3D Gauss-Markov mobility model." In MILCOM 2011 - 2011 IEEE Military Communications Conference. IEEE, 2011. http://dx.doi.org/10.1109/milcom.2011.6127781.

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Gouda, Bhabani Sankar, Pinaki Prasad Panigrahi, and Rabindra Kumar Shial. "Efficient Optimal Route Stability Routing Protocol in MANET Using Gauss-Markov Mobility Model." In 2013 Third International Conference on Advances in Computing and Communications (ICACC). IEEE, 2013. http://dx.doi.org/10.1109/icacc.2013.95.

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Reports on the topic "Gauss Markov model with constraints"

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Alenazi, Mohammed, Cenk Sahin, and James P. Sterbenz. Design Improvement and Implementation of 3D Gauss-Markov Mobility Model. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada582755.

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Schunk, Robert W. USU Gauss-Markov Model: High Resolution Regional Capability and Support for AFWA. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada613100.

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