Results 281 to 290 of about 9,151,209 (331)

IoV-based collision avoidance by using confidence region

2019 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE), 2019
For some IoV-based collision avoidance architectures, it is not necessary that all vehicles have communication ability. Hence, they need some particular designs and extra components.
Che-Cheng Chang, Chuan-An Lai, Wei-Ming Lin   +2 more
semanticscholar   +1 more source

Empirical likelihood-based unified confidence region for a predictive regression model

Communications in statistics. Simulation and computation, 2019
In finance and economics, predictive regression models are widely used. It is known that the limit distributions of their least squares estimators are nonstandard, and depend on the properties of the predictors.
Xiaohui Liu, Yuzi Liu, Fucai Lu
semanticscholar   +1 more source

Asymptotic Theory and Unified Confidence Region for an Autoregressive Model

Journal of Time Series Analysis, 2018
Although some unified inferences for the coefficient in an AR(1) model have been proposed in the literature, it remains open as to how to construct a unified confidence region for the intercept and the coefficient jointly without a prior on whether the ...
Xiaohui Liu, L. Peng
semanticscholar   +1 more source

Weakly Supervised Semantic Segmentation via Progressive Confidence Region Expansion

Computer Vision and Pattern Recognition
Weakly supervised semantic segmentation (WSSS) has garnered considerable attention due to its effective reduction of annotation costs. Most approaches utilize Class Activation Maps (CAM) to produce pseudo-labels, thereby localizing target regions using ...
Xiangfeng Xu, Pinyi Zhang, Wenxuan Huang, Yunhang Shen, Haosheng Chen, Jingzhong Lin, Wei Li, Gaoqi He, Jiao Xie, Shaohui Lin   +9 more
semanticscholar   +1 more source

CONFIDENCE REGIONS FOR REGRESSION PARAMETERS

Australian Journal of Statistics, 1962
SummarySuggestions for combining confidence interval estimates and extensions of the procedures to the determination of confidence regions for regression curves have been put forward. The merit of these ideas is believed to lie in their simplicity and potential wide applicability to a variety of regression problems.
openaire   +2 more sources

A new class of asymptotically valid confidence regions confidence regions

2011 International Conference on Consumer Electronics, Communications and Networks (CECNet), 2011
Weerahandi introduced the concept of generalized confidence intervals, which are to develop interval estimation. But it is difficult to use this method for constructing generalized confidence regions of vector parameters. In this paper we give a new method based on generalized bootstrap variable to construct asymptotically correct confidence regions of
openaire   +1 more source

Confidence Regions for Distribution Bounds

IEEE Transactions on Reliability, 1980
This paper considers the problem of constructing an s-confidence region for a pair of parameters which together mark the bounds of a distribution. The problem is solved, and a table provided, for a rectangular distribution; the solution is then generalized.
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ON THE CONSTRUCTION OF BOUNDS CONFIDENCE REGIONS

Econometric Theory, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Confidence Regions for Spectral Peak Frequencies

Biometrical Journal, 1997
AbstractA procedure is proposed to obtain confidence regions for spectral peak frequencies. The method is based on resampling the periodogram from the estimated spectrum in order to reestimate the spectrum and its peak frequency. We investigate the dependence of the results from the applied spectral estimator in three simulation studies and apply the ...
Timmer, Jens, Lauk, Michael, Lücking, Carl H.   +2 more
openaire   +2 more sources

Confidence regions for spectral bounds

ICASSP '84. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
Existing variance calculations for spectral estimates are unsatisfactory in that they depend upon information that is usually unavailable in practice. Some recent work in spectral estimation has involved the computation of bounds on the average spectral density in some region from a true correlation matrix.
openaire   +1 more source