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Covariance function
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251	ITSM-R Reference Manual George Weigt [removed] November 11, 2013 Contents Add to Reading List Source URL: eigenmath.sourceforge.net Language: English - Date: 2014-12-07 12:48:19 Covariance and correlation Error Measurement Partial autocorrelation function Autoregressive integrated moving average Errors and residuals in statistics Time series Variance Autoregressive–moving-average model Statistics Regression analysis Time series analysis
252	PHYSICAL REVIEW B 90, [removed]Current noise cross correlation mediated by Majorana bound states Hai-Feng L¨u,1,2 Hai-Zhou Lu,2 and Shun-Qing Shen2 1 Add to Reading List Source URL: web.hku.hk Language: English - Date: 2014-11-12 00:33:01 Physics Time series analysis Correlation function Spatial data analysis Dimensional analysis GF method Cross-correlation Entropy Statistics Covariance and correlation Chemistry
253	Hydrol. Earth Syst. Sci., 13, 1699–1712, 2009 www.hydrol-earth-syst-sci.net/ © Author(sThis work is distributed under the Creative Commons Attribution 3.0 License. Hydrology and Add to Reading List Source URL: www.hydrol-earth-syst-sci.net Language: English - Date: 2014-12-04 02:30:59 Water Statistical dependence Correlation and dependence Correlation function Drainage basin Correlation Information Covariance and correlation Statistics
254	Notes on nonseasonal ARIMA models Robert Nau Fuqua School of Business, Duke University 1. THE GENERAL THEORY So far we have looked at several different classes of models that might be used to predict a time Add to Reading List Source URL: people.duke.edu Language: English - Date: 2014-10-30 13:49:35 Noise Partial autocorrelation function Econometrics Regression analysis Moving-average model Autoregressive integrated moving average Autocorrelation Time series Data transformation Statistics Time series analysis Covariance and correlation
255	2012 IEEE/RSJ International Conference on Intelligent Robots and Systems October 7-12, 2012. Vilamoura, Algarve, Portugal Bayesian Optimisation for Intelligent Environmental Monitoring Roman Marchant and Fabio Ramos Add to Reading List Source URL: www-personal.acfr.usyd.edu.au Language: English - Date: 2015-01-05 23:35:39 Covariance and correlation Data analysis Root-mean-square deviation Gaussian process Normal distribution Covariance function Variance Spatial analysis Regression analysis Statistics Geostatistics Spatial data analysis
256	Multi-Task Learning of System Dynamics with Maximum Information Gain Jose F. Zubizarreta-Rodriguez and Fabio Ramos Australian Centre for Field Robotics, School of Information Technologies The University of Sydney, Austra Add to Reading List Source URL: www-personal.acfr.usyd.edu.au Language: English - Date: 2015-01-05 23:35:42 Exponentials Gaussian function Supervised learning Normal distribution Kriging Regression analysis Gaussian process Covariance matrix Control theory Statistics Data analysis Interpolation
257	GIGS[removed]Appendix (black font) Add to Reading List Source URL: static.berkeleyearth.org Language: English - Date: 2015-01-16 13:52:51 Spatial data analysis Interpolation Kriging Multivariate interpolation Correlation and dependence Covariance function Regression analysis Variance Covariance Statistics Covariance and correlation Geostatistics
258	Accounting for Atmospheric motion Vector Error Correlations in the ECMWF 4D-Var and Ensembles of Data Assimilations Lars Isaksen and Gábor Radnóti ECMWF, Reading, UK Add to Reading List Source URL: cimss.ssec.wisc.edu Language: English - Date: 2010-03-02 03:21:04 Correlation function Data assimilation G factor Statistics Covariance and correlation Correlation and dependence
259	This is page 365 Printer: Opaque this Chapter 15 Cluster-Weighted Modeling: Probabilistic Time Series Prediction, Characterization Add to Reading List Source URL: cba.mit.edu Language: English - Date: 2011-12-13 18:32:02 Estimation theory Regression analysis Statistical theory Cluster-weighted modeling Expectation–maximization algorithm Gaussian function Normal distribution Covariance matrix Generalized linear model Statistics Multivariate statistics Data analysis
260	Bayesian Optimisation for Active Perception and Smooth Navigation Jefferson R. Souza, Roman Marchant, Lionel Ott, Denis F. Wolf and Fabio Ramos Abstract— A key challenge for long-term autonomy is to enable a robot to a Add to Reading List Source URL: www-personal.acfr.usyd.edu.au Language: English - Date: 2015-01-05 23:35:48 Covariance function Spatial data analysis Kriging Vibration Robotics Mixture model Wavelet Gaussian process Regression analysis Statistics Geostatistics Covariance and correlation

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