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A Geometric Calibration Method of Hydrophone Array Based on Maximum Likelihood Estimation with Sources in Near Field

Nan Zou, Zhenqi Jia, Jin Fu, Jia Feng, Mengqi Liu
2020 Journal of Marine Science and Engineering  
According to the near-field geometry error model, the objective function of nonlinear optimization problem is constructed by using the unconditional maximum likelihood estimator.  ...  It can be used as both auxiliary-calibration and self-calibration.  ...  Using the non-conditional maximum likelihood estimator, we construct an objective function, and the DE method are used to solve the problem of near-field calibration.  ... 
doi:10.3390/jmse8090678 fatcat:dwhpfqpb5ncsvemtesk33h6fhy

Array calibration for mutual coupling errors of high-frequency surface wave radar

Long Chao, Wu Xiongbin, Liu Bin, Li Lun, Xu Xing'an
2012 IEICE Electronics Express  
This method converts array error estimation into joint estimation of multi-parameters and gets the optimal solution estimation by using improved hybrid algorithm.  ...  Simulation results and field experiment data show that this method significantly improves the performance of spatial spectrum algorithm in the array calibration for mutual coupling errors of distributed  ...  Furthermore we use the combination of AHA and sea echo method to achieve array calibration for mutual coupling errors of high-frequency radar without extra auxiliary source.  ... 
doi:10.1587/elex.9.731 fatcat:dgaltopsnbfhbhknido3r373nu

Maximum Entropy Estimation for Survey sampling [article]

Fabrice Gamboa (Méthodes d'Analyse Stochastique des Codes et Traitements Numériques), Jean-Michel Loubes
2009 arXiv   pre-print
This method points a new frame for the computation of such estimates and the investigation of its statistical properties.  ...  Finding the optimal weights is achieved by considering random weights and looking for a discrete distribution which maximizes an entropy under the calibration constraint.  ...  Reducing the dimension of the problem is made by choosing the proper real-valued auxiliary variable, and therefore, the proper one-dimensional linear subspace on which y is projected.  ... 
arXiv:0909.4046v1 fatcat:hf66dx2umzfrtjgyiugg6nxuqm

Maximum entropy estimation for survey sampling

Fabrice Gamboa, Jean-Michel Loubes, Paul Rochet
2011 Journal of Statistical Planning and Inference  
This method points a new frame for the computation of such estimates and the investigation of its statistical properties.  ...  Finding the optimal weights is achieved by considering random weights and looking for a discrete distribution which maximizes an entropy under the calibration constraint.  ...  Reducing the dimension of the problem is made by choosing the proper real-valued auxiliary variable, and therefore, the proper one-dimensional linear subspace on which y is projected.  ... 
doi:10.1016/j.jspi.2010.06.002 fatcat:djoqein7lncn3lk6k2ndvccfbq

Learning a high-dimensional classification rule using auxiliary outcomes [article]

Muxuan Liang, Xiang Zhong, Jaeyoung Park
2020 arXiv   pre-print
presence of auxiliary outcomes in high-dimensional settings.  ...  The proposed method includes a pooled estimation step using all outcomes to gain efficiency, and a subsequent calibration step using only the outcome of interest to correct both types of biases.  ...  The function G(·) is the cumulative distribution function of a standard normal distribution.  ... 
arXiv:2011.05493v1 fatcat:fxclcuqeszhphifowzvilvospm

CODA: Calibrated Optimal Decision Making with Multiple Data Sources and Limited Outcome [article]

Hengrui Cai, Wenbin Lu, Rui Song
2021 arXiv   pre-print
We consider the optimal decision-making problem in a primary sample of interest with multiple auxiliary sources available.  ...  This paper proposes a new framework to handle heterogeneous studies and address the limited outcome simultaneously through a novel calibrated optimal decision making (CODA) method, by leveraging the common  ...  Different from existing calibration estimators, the proposed calibrated value estimator is a function of the decision rule and needs to be maximized over a class of decision rules to find the estimated  ... 
arXiv:2104.10554v3 fatcat:i44x5p3t2jfvjf2jdmntcic4r4

Bending the Curve: Improving the ROC Curve Through Error Redistribution [article]

Oran Richman, Shie Mannor
2016 arXiv   pre-print
We propose an algorithm for the derivation of optimal thresholds by redistributing the error depending on features that hold information about difficulty.  ...  Features that hold information about the "difficulty" of the data may be non-discriminative and are therefore disregarded in the classification process.  ...  and p − (x) should be estimated. All of these functions can be estimated using conventional parametric estimation methods (For example, maximizing the log likelihood).  ... 
arXiv:1605.06652v1 fatcat:fzobvuc2wvcz7nnmykpzwknrjm

Exact prior-free probabilistic inference on the heritability coefficient in a linear mixed model

Qianshun Cheng, Xu Gao, Ryan Martin
2014 Electronic Journal of Statistics  
In particular we construct exact confidence intervals and demonstrate numerically our method's efficiency compared to that of existing methods.  ...  of total variability due to the biological effect.  ...  Acknowledgements The authors thank Chuanhai Liu for helpful comments and suggestions. This work is partially supported by the U.S. National Science Foundation, grant DMS-1208833.  ... 
doi:10.1214/15-ejs984 fatcat:i24ce5vxyvcs5g7p3dbwp5t2su

Application of a Hybrid Interpolation Method Based on Support Vector Machine in the Precipitation Spatial Interpolation of Basins

Xiaoxiao Zhang, Guodong Liu, Hantao Wang, Xiaodong Li
2017 Water  
In this paper, we applied the support vector machine (SVM) to the spatial interpolation of the multi-year average annual precipitation in the Three Gorges Region basin.  ...  ; (2) the support vector machine hybrid interpolation method obtains superior interpolation results compared to the inverse distance weighting method, ordinary kriging method and linear regression hybrid  ...  The key is to map the original dataset, as the training set data, into a high-dimensional linear feature space through the nonlinear function φ(x) and construct the regression estimation function in the  ... 
doi:10.3390/w9100760 fatcat:565avohtyzetxbzfojxmkylysq

Indirect Inference: Which Moments to Match?

David Frazier, Eric Renault
2019 Econometrics  
recently identified vector of estimating equations.  ...  The standard approach to indirect inference estimation considers that the auxiliary parameters, which carry the identifying information about the structural parameters of interest, are obtained from some  ...  of g(·) and the dimension of β coincide.  ... 
doi:10.3390/econometrics7010014 fatcat:2gz72a3at5galnae6p5g3mk4uq

Neural Architecture Search for Efficient Uncalibrated Deep Photometric Stereo [article]

Francesco Sarno, Suryansh Kumar, Berk Kaya, Zhiwu Huang, Vittorio Ferrari, Luc Van Gool
2021 arXiv   pre-print
We then perform a continuous relaxation of this search space and present a gradient-based optimization strategy to find an efficient light calibration and normal estimation network.  ...  We begin by defining a discrete search space for a light calibration network and a normal estimation network, respectively.  ...  At train time, we regularize the normal estimation network loss function using the concept of auxiliary tower [39] for performance gain.  ... 
arXiv:2110.05621v1 fatcat:jayzvx6cnfflnpscfik35eh76m

Connections between Survey Calibration Estimators and Semiparametric Models for Incomplete Data

Thomas Lumley, Pamela A. Shaw, James Y. Dai
2011 International Statistical Review  
In this paper we relate the survey calibration estimators to the semiparametric incomplete-data estimators of Robins and coworkers, and to adjustment for baseline variables in a randomized trial.  ...  Survey calibration (or generalized raking) estimators are a standard approach to the use of auxiliary information in survey sampling, improving on the simple Horvitz-Thompson estimator.  ...  Even with the optimal choice of functions φ, the class of AIPW estimators, and thus of calibration estimators, need not include the semiparametric efficient estimator.  ... 
doi:10.1111/j.1751-5823.2011.00138.x pmid:23833390 pmcid:PMC3699889 fatcat:hk2pl7ywwvcmfmqgkpnbn3bw4y

iDQ: Statistical Inference of Non-Gaussian Noise with Auxiliary Degrees of Freedom in Gravitational-Wave Detectors [article]

Reed Essick, Patrick Godwin, Chad Hanna, Lindy Blackburn, Erik Katsavounidis
2020 arXiv   pre-print
signal and thousands of auxiliary degrees of freedom.  ...  In particular, we construct a likelihood-ratio test that simultaneously accounts for the presence of non-Gaussian noise artifacts and utilizes information from both the observed gravitational-wave strain  ...  ACKNOWLEDGMENTS The authors thank Ruslan Vaulin and acknowledge his vital contributions to earlier versions of iDQ. R.  ... 
arXiv:2005.12761v1 fatcat:oddixjuwbbar5gt36avl24sibe

Stochastic simulation framework for the Limit Order Book using liquidity motivated agents [article]

Efstathios Panayi, Gareth Peters
2015 arXiv   pre-print
We develop an efficient way to perform statistical calibration of the model parameters on Level 2 limit order book data from Chi-X, based on a combination of indirect inference and multi-objective optimisation  ...  We then demonstrate how such an agent-based modelling framework can be of use in testing exchange regulations, as well as informing brokerage decisions and other trading based scenarios.  ...  Acknowledgements EP acknowledges the support of Prof. Mark Harman for discussions on agent-based modelling and initial work on calibration through multi-objective optimisation.  ... 
arXiv:1501.02447v3 fatcat:3zdu4teht5didii5iijhvlplly

An accurate and robust gaze estimation method based on Maximum Correntropy Criterion

Ben Yang, Xuetao Zhang, Zhongchang Li, Shaoyi Du, Fei Wang
2019 IEEE Access  
To address the problems, we adopt a mapping relationship between the high-dimensional eye image features space and the low-dimensional gaze positions and propose a robust and accurate method for gaze estimation  ...  Then, we construct the objective function using the maximum correntropy criterion instead of mean squared error, which can enhance the anti-noise ability, especially for outliers or pixel corruption.  ...  the weight vector w = E Tê ; 2: Update the weight vector w and the auxiliary variables p; 3: for τ = 1 to n do 4: Update the auxiliary variables p by ((24)); 5: Update the weight vector by ( (27  ... 
doi:10.1109/access.2019.2896303 fatcat:arq544q7fndkbkax3fqjjcdyku
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