Academic literature on the topic 'Auto regression'
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Journal articles on the topic "Auto regression"
Alhassan, Baba Gimba. "Improving Forecasting Using Vector Auto Regression Approach on Tax Revenue." Journal of Advanced Research in Dynamical and Control Systems 12, SP7 (July 25, 2020): 294–303. http://dx.doi.org/10.5373/jardcs/v12sp7/20202110.
Full textHolden, Ken. "Vector auto regression modeling and forecasting." Journal of Forecasting 14, no. 3 (May 1995): 159–66. http://dx.doi.org/10.1002/for.3980140302.
Full textBakouch, Hassan, Miroslav Ristic, E. Sandhya, and S. Satheesh. "Random products and product auto-regression." Filomat 27, no. 7 (2013): 1197–203. http://dx.doi.org/10.2298/fil1307197b.
Full textDimitriou-Fakalou, Chrysoula. "The auto-regression and the moving-average." Journal of Statistical Planning and Inference 140, no. 7 (July 2010): 1739–43. http://dx.doi.org/10.1016/j.jspi.2009.12.022.
Full textFernández-García, María-Elena, José-Luis Sancho-Gómez, Antonio Ros-Ros, and Aníbal R. Figueiras-Vidal. "Complete Stacked Denoising Auto-Encoders for Regression." Neural Processing Letters 53, no. 1 (January 12, 2021): 787–97. http://dx.doi.org/10.1007/s11063-020-10419-0.
Full textZeng, Shan. "Application Examples of Auto-Regression and Subsection-Regression for Tunnel Distortion Analysis." Advanced Materials Research 639-640 (January 2013): 233–38. http://dx.doi.org/10.4028/www.scientific.net/amr.639-640.233.
Full textBaraud, Yannick, F. Comte, and G. Viennet. "Model selection for (auto-)regression with dependent data." ESAIM: Probability and Statistics 5 (2001): 33–49. http://dx.doi.org/10.1051/ps:2001101.
Full textVaragouli, E. G., T. E. Simos, G. Giannopoulos, B. Stefanis, and G. S. Xeidakis. "Regression models for intercity auto directional travel demand." Journal of Statistics and Management Systems 4, no. 1 (January 2001): 1–28. http://dx.doi.org/10.1080/09720510.2001.10701023.
Full textLuo, Z. "Pavement performance modelling with an auto-regression approach." International Journal of Pavement Engineering 14, no. 1 (January 2013): 85–94. http://dx.doi.org/10.1080/10298436.2011.617442.
Full textSmyth, Christine, Danny Coomans, Yvette Everingham, and Timothy Hancock. "Auto-associative Multivariate Regression Trees for Cluster Analysis." Chemometrics and Intelligent Laboratory Systems 80, no. 1 (January 2006): 120–29. http://dx.doi.org/10.1016/j.chemolab.2005.09.001.
Full textDissertations / Theses on the topic "Auto regression"
Medeiros, Patrick Valverde. "Análise da evapotranspiração de referência a partir de medidas lisimétricas e ajuste estatístico de estimativas de nove equações empírico-teóricas com base na equação de Penman-Monteith." Universidade de São Paulo, 2008. http://www.teses.usp.br/teses/disponiveis/18/18138/tde-21052008-090008/.
Full textThe quantification of the evapotranspiration is an essential task for the determination of the water balance in a watershed and for the establishment of the culture´s water deficit. Therefore, the present work describes the analysis of the reference evapotranspiration (ETo) for the region of Jaboticabal-SP. The phenomenon behavior in the region was studied based on the interpretation of 12 drainage lysimeters data (EToLis) and on theoretical estimates for 10 different equations available in the Literature. An statistical analysis indicated that the theoretical ETo estimates compared with the EToLis did not present good indices of comparison and error. Admitting that the lysimeters operation did not allow a reliable ETo determination, a local adjustment of the theoretical methodologies for ETo estimate was considered. An auto-regression (AR) of the noises of these equations in comparison with the annual average estimate for the Penman-Monteith equation (EToPM), taken as standard, has been performed in fortnightly and monthly periods. The adjustment through simple linear regression has also been analyzed. The obtained results indicate that the effective radiation is the most important climatic variable for the establishment of the ETo in the region. The Penman-Monteith estimate presented excellent correlation to the estimates by Makkink (1957) equation and the energy balance. The local adjustments presented excellent results for the majority of the tested equations, specially for the solar radiation FAO-24, Makkink (1957), Jensen-Haise (1963), Camargo (1971), radiation balance, Turc (1961) and Thornthwaite (1948) equations. The adjustment by simple linear regression is of easier execution and also presented excellent results.
Alfuhaid, Abdulaziz Ataallah. "AN AGENT-BASED SYSTEMATIC ENSEMBLE APPROACH FOR AUTO AUCTION PREDICTION." University of Akron / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=akron1542560217326084.
Full textHagos, Tesfamichael Marikos. "Estimation of phases for compliant motion : Auto-regressive HMM, multi-class logistic regression, Learning from Demonstration (LfD), Gradient descent optimization." Thesis, Luleå tekniska universitet, Rymdteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-65613.
Full textDhankhar, Rashmi. "Effects of expansionary monetary policy shocks on financial variables." Thesis, Manhattan, Kan. : Kansas State University, 2010. http://hdl.handle.net/2097/3517.
Full textAlkan, Feyza. "The Sustainability Analysis Of Turkish Domestic Debt." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/2/12611159/index.pdf.
Full textsustainability indicators&rdquo
perspective. The fiscal targets of Maastricht Treaty (1992) are imposed on the Turkish fiscal policy and it is investigated whether these targets are the indicators for sustainability in the medium term. Uctum and Wickens&rsquo
(2000) methodology is followed in assessing the sustainability of the current fiscal policy and the efficiency of the Maastricht Treaty (1992) targets. Moreover, the vector auto regression (VAR) approach of Garcia and Rigobon (2004) is utilized in deriving the econometric model for the debt dynamics of Turkey. The results suggest that domestic debt of Turkey has been unsustainable within 1994-2008. Furthermore, the Maastricht Treaty (1992) fiscal targets are binding for Turkey and gaining more significance in the recent years.
Hentic-Giliberto, Michelle. "Les caractéristiques des auto-entrepreneurs bretons : comparaison avec les autres entrepreneurs." Thesis, Brest, 2014. http://www.theses.fr/2014BRES0023/document.
Full textWhile mutations accelerate and instability seems to be permanent, entrepreneurship is valued by public and private actors. In France, the auto-entrepreneur, created by Law No. 2008-776 of 4 August 2008, promotes access to entrepreneurship to greater numbers. Since 2009, the auto-entrepreneurs account for more than half of self-employed entrepreneurs. Also, the existence of a specific entrepreneurial approach to business creation projects under this status arises. This research is part of a constructivist approach to explain the phenomenon by identifying the characteristics of auto-entrepreneurs in comparison to other entrepreneurs. It is rooted in the examination of 700 projects evaluated in upstream phase of the creation / buyout in the southern Finistère, from late 2008 to early 2012, almost 1% of the creation / buyout firms on the Brittany area. The support of entrepreneurial paradigms leads to closer generic theoretical standard to findings from the field. A counterfactual approach identifies the characteristics of auto-entrepreneurs in comparison to other entrepreneurs. Thematic qualitative analysis of biographical interviews of auto-entrepreneurs triangulates and confirms the results. The research questions the paradigm of creating / obtaining new or existing value. She questions the Schumpeterian process of creative versus destructive innovation, and its possible mobilization in a reading of the success of the auto-entrepreneur. It offers effectual approach creation depending on the status of auto-entrepreneur. It confirms the role of the accompanying upstream phase of the creation / buyout business
Akkoyunlu, Sule. "Turkish consumption and saving." Thesis, University of Oxford, 2000. http://ora.ox.ac.uk/objects/uuid:0ba100a8-0a19-40f5-a7c6-c18aa010c130.
Full textFransson, Martin. "Identification of a Genetic Network in the Budding Yeast Cell Cycle." Thesis, Linköping University, Department of Electrical Engineering, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2389.
Full textBy using AR/ARX-models on data generated by a nonlinear differential equation system representing a model for the cell-cycle control system in budding yeast, the interactions among proteins and thereby also to some extent the genes, are sought. A method consisting of graphical analysis of differences between estimates from two local linear models seems to make it possible to separate a set of linear equations from the nonlinear system. By comparing the properties of the estimations in the linear equations a set of approximate equations corresponding well to the real ones are found.
A NARX model is tested on the same system to see whether it is possible to find the dependencies in one of the nonlinear differential equations. This approach did, for the choice of model, not work.
Kollár, Miroslav. "Macrofinance Modeling from Asset Allocation Perspective." Doctoral thesis, Vysoká škola ekonomická v Praze, 2006. http://www.nusl.cz/ntk/nusl-79535.
Full textTiftik, Mehmet Emre. "Assessing Domestic Debt Sustainability Of Turkey With A Risk Management Approach." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/3/12607632/index.pdf.
Full texts (1989) methodology and Uctum and Wicken'
s (2000) methodology in order to assess the fiscal sustainability of Turkey.
Books on the topic "Auto regression"
Lloyd, Tim. Testing a capital pricing model of land values: Cointegration and error correction in a vector auto-regression. Nottingham: Department of Economics, University of Nottingham, 1992.
Find full textSkinner, Gregory H. Two-dimensional auto-regressive modeling. Monterey, Calif: Naval Postgraduate School, 1989.
Find full textIshiguro, M. ARdock, an auto-regressive model analyzer. Tokyo: Institute of Statistical Mathematics, 1999.
Find full textIshiguro, M. ARdock, an auto-regressive model analyzer. Tokyo: Institute of Statistical Mathematics, 1999.
Find full textSkalin, Joakim. Modelling macroeconomic time series with smooth transition auto regressions. Stockholm: Stockholm School of Economics, 1999.
Find full textBurridge, Peter. Forecasting and signal extraction in auto regressive-moving average models. Coventry: University of Warwick,Department of Economics, 1986.
Find full textBerg, Andrew, and Rafael Portillo. Introduction to Part I. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198785811.003.0003.
Full textKobylinska-Dehe, Ewa, Pawel Dybel, and Ludger M. Hermanns, eds. Wiederkehr des Verdrängten? Psychosozial-Verlag, 2020. http://dx.doi.org/10.30820/9783837977325.
Full textDampak reformasi nilai tukar rupiah terhadap tingkat inflasi dan neraca perdagangan Indonesia: Suatu pendekatan model vektor auto regressive : laporan penelitian dosen muda. [Jambi]: Fakultas Ekonomi, Universitas Jambi, 2007.
Find full textBook chapters on the topic "Auto regression"
Sisman-Yilmaz, N. Arzu, Ferda N. Alpaslan, and Lakhmi C. Jain. "Fuzzy Multivariate Auto-Regression Method and its Application." In Studies in Fuzziness and Soft Computing, 281–300. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-39972-8_9.
Full textRavi, Vadlamani, and Amit Yadav. "Privacy Preserving Data Mining Using General Regression Auto-Associative Neural Network: Application to Regression Problems." In Swarm, Evolutionary, and Memetic Computing, 618–24. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20294-5_53.
Full textLu, Yu-zhen, Ming-hui Qu, and Min Zhang. "An Application of Dynamic Regression Model and Residual Auto-Regressive Model in Time Series." In Advances in Neural Networks – ISNN 2014, 222–31. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12436-0_25.
Full textPirhonen, Mikko, Olli Suominen, and Antti Vehkaoja. "Auto-regression-driven, reallocative particle filtering approaches in PPG-based respiration rate estimation." In EMBEC & NBC 2017, 1020–24. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5122-7_255.
Full textTaghavi, Majid. "Debt, growth and inflation in large European economies: a vector auto-regression analysis." In Capitalism and Democracy in the 21st Century, 165–79. Heidelberg: Physica-Verlag HD, 2001. http://dx.doi.org/10.1007/978-3-662-11287-8_9.
Full textYao, Ping. "Integrating Generalized Linear Auto-Regression and Artificial Neural Networks for Coal Demand Forecasting." In Advances in Neural Networks – ISNN 2009, 993–1001. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01507-6_112.
Full textKazar, Baris M., Shashi Shekhar, David J. Lilja, Ranga R. Vatsavai, and R. Kelley Pace. "Comparing Exact and Approximate Spatial Auto-regression Model Solutions for Spatial Data Analysis." In Geographic Information Science, 140–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30231-5_10.
Full textJin, Xiangyang, Shisheng Zhong, Gang Ding, and Lin Lin. "Engine Testing Fault Classification Based on the Multi-class SVM of Auto-regression." In Lecture Notes in Electrical Engineering, 33–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-26001-8_5.
Full textNayak, Archana M., and Nirbhay Chaubey. "Predicting Passenger Flow in BTS and MTS Using Hybrid Stacked Auto-encoder and Softmax Regression." In Communications in Computer and Information Science, 29–41. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6648-6_3.
Full textRavi, Vadlamani, and Ranabir De. "Principal Component Analysis and General Regression Auto Associative Neural Network Hybrid as One-Class Classifier." In Swarm, Evolutionary, and Memetic Computing, 164–75. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20294-5_15.
Full textConference papers on the topic "Auto regression"
Runkler, Thomas A., and Hans Georg Seedig. "Fuzzy c-auto regression models." In 2008 IEEE 16th International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2008. http://dx.doi.org/10.1109/fuzzy.2008.4630617.
Full textPriya, S. Selva, and Lavanya Gupta. "Predicting the future in time series using auto regressive linear regression modeling." In 2015 Twelfth International Conference on Wireless and Optical Communications Networks (WOCN). IEEE, 2015. http://dx.doi.org/10.1109/wocn.2015.8064521.
Full textLi, Qianru, Christophe Tricaud, Rongtao Sun, and YangQuan Chen. "Great Salt Lake Surface Level Forecasting Using FIGARCH Model." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-34909.
Full textTomar, Nimisha, Durga Patel, and Akshat Jain. "Air Quality Index Forecasting using Auto-regression Models." In 2020 IEEE International Students' Conference on Electrical,Electronics and Computer Science (SCEECS). IEEE, 2020. http://dx.doi.org/10.1109/sceecs48394.2020.216.
Full textVaragnolo, Damiano, Gianluigi Pillonetto, and Luca Schenato. "Auto-tuning procedures for distributed nonparametric regression algorithms." In 2015 European Control Conference (ECC). IEEE, 2015. http://dx.doi.org/10.1109/ecc.2015.7330614.
Full textHu, Jianfeng, and Zhendong Mu. "EEG authentication system based on auto-regression coefficients." In 2016 10th International Conference on Intelligent Systems and Control (ISCO). IEEE, 2016. http://dx.doi.org/10.1109/isco.2016.7727122.
Full textAnguita, Davide, Luca Ghelardoni, and Alessandro Ghio. "Long-term energy load forecasting using Auto-Regressive and approximating Support Vector Regression." In 2012 IEEE International Energy Conference (ENERGYCON 2012). IEEE, 2012. http://dx.doi.org/10.1109/energycon.2012.6348269.
Full textLiu, Qian-qian, and Hong-xia Wang. "Study on fault forecasting based on auto-regression model." In 2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). IEEE, 2015. http://dx.doi.org/10.1109/iaeac.2015.7428733.
Full textFan, Wei, Feng Ding, and Yang Shi. "Parameter Estimation for Hammerstein Nonlinear Controlled Auto-Regression Models." In 2007 IEEE International Conference on Automation and Logistics. IEEE, 2007. http://dx.doi.org/10.1109/ical.2007.4338714.
Full textPu, Tiecheng, and Jing Bai. "An auto regression compression method for industrial real time data." In 2014 26th Chinese Control And Decision Conference (CCDC). IEEE, 2014. http://dx.doi.org/10.1109/ccdc.2014.6853094.
Full textReports on the topic "Auto regression"
Julio, Juan. Estimating the Exchange Rate Pass-Through: A Time-Varying Vector Auto-Regression with Residual Stochastic Volatility Approach. Banco de la República de Colombia, October 2019. http://dx.doi.org/10.32468/be.1093.
Full textMychal, Myron R., and Donald R. Ucci. Robust Locally Optimum Detection in Auto-Regressive Noise. Fort Belvoir, VA: Defense Technical Information Center, August 1999. http://dx.doi.org/10.21236/ada369115.
Full text