286,797 Hits in 6.5 sec

Statistical efficiency of curve fitting algorithms [article]

N. Chernov, C. Lesort
2003 arXiv   pre-print
We study the problem of fitting parametrized curves to noisy data.  ...  We then show that the gradient-weighted algebraic fit is statistically efficient and describe all other statistically efficient algebraic fits.  ...  Efficiency of circle fitting algorithms. Data are sampled along a full circle.  ... 
arXiv:cs/0303015v1 fatcat:njuvtniib5eznmcjaomml5j6ou

Statistical efficiency of curve fitting algorithms

N. Chernov, C. Lesort
2004 Computational Statistics & Data Analysis  
We study the problem of fitting parametrized curves to noisy data.  ...  We then show that the gradient-weighted algebraic fit is statistically efficient and describe all other statistically efficient algebraic fits.  ...  Efficiency of circle fitting algorithms. Data are sampled along a full circle.  ... 
doi:10.1016/j.csda.2003.11.008 fatcat:arercr4v2be5nmh2g6d3t7znem

A comparative study of curve-fitting algorithms used for radiation detection efficiencies

E.-M. Lykiardopoulou, A. Khaliel, Theo J. Mertzimekis
2017 Figshare  
Main focus of the test was to investigate any variations in the resulting values of the fitting parameters, as well as their respective statistical errors.  ...  Comparative plots Conclusions Efficiency curve fitting was performed in five different software environments.  ... 
doi:10.6084/m9.figshare.5072245.v1 fatcat:4wicfqfyufdl5ouuhstrddlayq

Eliminating Noise at the Box-fitting Spectrum

Rodrigo Carlos Boufleur, Marcelo Emilio, Eduardo Janot Pacheco, Jorge Ramiro de La Reza, José Carlos da Rocha
2012 Proceedings of the International Astronomical Union  
In this work we show that a modified detrend algorithm CDA (CoRoT Detrend Algorithm; Mislis et al. 2010) using a robust statistics and an empirical fit, instead of a polynomial one, can eliminate more  ...  efficiently gaps in the data and other long-term trends from the light-curve.  ...  We replace the polynomial fit by a resistant moving average in order to increase the sensitivity to sudden fluctuations in the data. We also implement a more robust statistics in the algorithm.  ... 
doi:10.1017/s1743921313013288 fatcat:vntrew6zdfdjne64jbdkc7kbxy

The Contracting Curve Density Algorithm: Fitting Parametric Curve Models to Images Using Local Self-Adapting Separation Criteria

Robert Hanek, Michael Beetz
2004 International Journal of Computer Vision  
In this article, we propose the Contracting Curve Density (CCD) algorithm as a solution to the curve-fitting problem. The CCD algorithm extends the state-of-the-art in two important ways.  ...  First, it applies a novel likelihood function for the assessment of a fit between the curve model and the image data.  ...  Acknowledgments: The authors would like to thank Carsten Steger for providing the DLL of the color edge detector; Jianbo Shi and Jitendra Malik for providing the executable of the Normalized Cuts algorithm  ... 
doi:10.1023/b:visi.0000025799.44214.29 fatcat:f5pylswvv5bh7jqrd7hn6vcita

Continuous Extraction of Subway Tunnel Cross Sections Based on Terrestrial Point Clouds

Zhizhong Kang, Liqiang Zhang, Lei Tuo, Baoqian Wang, Jinlei Chen
2014 Remote Sensing  
First, the continuous central axis of the tunnel is extracted using a 2D projection of the point cloud and curve fitting using the RANSAC (RANdom SAmple Consensus) algorithm, and the axis is optimized  ...  An efficient method for the continuous extraction of subway tunnel cross sections using terrestrial point clouds is proposed.  ...  Figure 10 . 10 Statistical test results of the optimized BaySAC algorithm. (a) Straight line; (b) Transition curve; (c) Curve.  ... 
doi:10.3390/rs6010857 fatcat:pihfq4vlbfgy3nwk67l7vzikci


Taskin Atilgan, Hamparsum Bozdogan
1990 Journal of the Japan Statistical Society, Japanese Issue  
Numerical examples are provided to illustrate the versatility and efficiency of the proposed approach by automating the curve fitting process.  ...  The EM algorithm is developed for a "mixture" of B-splines to obtain the maxi mum likelihood estimators of the parameters and to score AIC.  ...  of our proposed new approach by automating the curve fitting process without any subjectivity.  ... 
doi:10.11329/jjss1970.20.179 fatcat:v6xva7y66ngjxaet2dsojcpmd4

Contrasting Two Frameworks for ROC Analysis of Ordinal Ratings

Daryl E. Morris, Margaret Sullivan Pepe, William E. Barlow
2010 Medical decision making  
algorithms and the efficiencies with which they use data.  ...  Background-Statistical evaluation of medical imaging tests used for diagnostic and prognostic purposes often employ receiver operating characteristic (ROC) curves.  ...  Acknowledgments Supported in part by R01 CA129934: Considerations of Covariates in Biomarker Studies and R01 GM054438: Statistical Methods for Medical Tests and Biomarkers by the National Institutes of  ... 
doi:10.1177/0272989x09357477 pmid:20147599 pmcid:PMC2905510 fatcat:ucd2jwns5jgz3gzzi4fwnqi7di

Fault Detection of a Wind Turbine's Gearbox, based on Power Curve Modeling and an on-line Statistical Change Detection Algorithm

Basheer W. Shaheen, Ahmed Abu Hanieh, István Németh
2021 Acta Polytechnica Hungarica  
Finally, an on-line CUSUM statistical change detection algorithm was used to evaluate and detect small changes in power residuals generated from the model.  ...  The presented fault detection system successfully detected faults in both detection levels under realistic wind turbulence and with a fault magnitude of 2% efficiency degradation for the progressive degradation  ...  Acknowledgment The authors would like to thank the Department of Control Engineering and System Analysis at the Free University of Brussels (ULB) and the head of department Prof.  ... 
doi:10.12700/aph.18.6.2021.6.10 fatcat:hvnnshov5bhmtftn4cae5su3oy

On the Use of Random Variables in Particle Swarm Optimizations: A Comparative Study of Gaussian and Uniform Distributions

L. Zhang, F. Yang, A. Z. Elsherbeni
2009 Journal Electromagnetic Waves and Applications  
It is revealed through the statistic analysis that the Gaussian distributed random variables increase the efficiency of the PSO algorithm as compared to the widely used uniformly distributed random variables  ...  The particle swarm optimization (PSO), now widely used in the electromagnetics community, is a robust evolutionary method based on the property of swarm intelligence.  ...  According to various statistical comparisons of the Rastrigin's function and an antenna array example, it is demonstrated that the PSO algorithm is more efficient when using the new proposed Gaussian random  ... 
doi:10.1163/156939309788019787 fatcat:5j4lbr7qcbaelibzz6ja4au6gy

Abstracts of Bulletin of the Computational Statistics of Japan

1992 Journal of the Japanese Society of Computational Statistics  
Hastie and Stuetzle (1989) have proposed Principal Curves as an algorithm to fit curves to such data.  ...  A Refined Algorithm of Principal Curves and the Evaluation of Its Complexity.  ... 
doi:10.5183/jjscs1988.5.75 fatcat:kucr5szxszcdzddj4dpmsd5kcm

Development of a prediction model based on linear regression to estimate the success rates of seafood caught from different catching centers

Sherimon et al., Department of Information Technology, University of Technology and Applied Sciences, Muscat, Oman
2021 International Journal of Advanced and Applied Sciences  
To determine the best model to match the data, the algorithms employ the Least-Square Curve Fitting approach. The success rates are predicted using the best-fit model that results.  ...  of the presented algorithms.  ...  This method of the curve fit is relatively straightforward and easy to compute and understand, but it is not the most statistically robust method of fitting a function.  ... 
doi:10.21833/ijaas.2021.12.013 fatcat:jagmtw65cfenhcglohvi2mh5ea

Flexible Hierarchical Gaussian Mixture Model for High-Resolution Remote Sensing Image Segmentation

Xue Shi, Yu Li, Quanhua Zhao
2020 Remote Sensing  
One effective way to improve the segmentation accuracy is to accurately model the statistical distributions of pixel intensities.  ...  The results show that the proposed algorithm is able to flexibly model the complicated distributions and accurately segment images.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs12071219 fatcat:wyrrpvqn7bfpha4f4ke7l22kf4

Improving RANSAC for Efficient and Precise Model Fitting with Statistical Analysis

Yunliang Zhang, Hengyuan Tian, Yanzi Deng, Jianguo Wang
2019 European Journal of Electrical Engineering and Computer Science  
RANSAC (random sample consensus) has been widely used as a benchmark algorithm for model fitting in the presence of outliers for more than thirty years.  ...  Many other algorithms have been proposed for the improvement of RANSAC.  ...  CONCLUSION This paper introduces a precise and efficient model fitting algorithm named as SASAC, which is based on statistical analysis for sample consensus.  ... 
doi:10.24018/ejece.2019.3.5.111 fatcat:t26uq2j6lba3zl4n4gfrxurini

An Efficient Approximation for Nakagami-m Quantile Function Based on Generalized Opposition-Based Quantum Salp Swarm Algorithm [chapter]

Hongyuan Gao, Yangyang Hou, Shibo Zhang, Ming Diao
2021 Prime Archives in Applied Mathematics  
In order to obtain the closed form expression that is able to fit the curve of Nakagami-m quantile function as well as possible, we adopt the method of curve fitting in this paper.  ...  In addition, the simulation results show that compared with existing curve-fitting-based methods, the proposed expression decreases the fitting error by roughly one order of magnitude in most cases and  ...  Meanwhile, he adopted backtracking search optimization algorithm and artificial bee colony optimization to solve this curve-fitting problem respectively.  ... 
doi:10.37247/paam2ed.2.2021.21 fatcat:b7dxupkwlvd5xc4dbkv7jz2vwa
« Previous Showing results 1 — 15 out of 286,797 results