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Bayesian estimation of rare sensitive attribute
Communications in Statistics - Simulation and Computation, 2015ABSTRACTRandomized response models have been used to estimate a population proportion of a sensitive attribute. A randomized device is typically employed to protect respondent's privacy in a survey. In addition, an unrelated question is asked to improve the statistical efficiency.
Joon Jin Song, Jong-Min Kim 0001
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Scalable visual sensitivity profile estimation
2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008We propose a computational model for estimating scalable visual sensitivity profile (SVSP) of video, which is a hierarchy of saliency maps that simulates the bottom-up and top- down attention of the human visual system (HVS). The bottom- up process considers low level stimulus-driven visual features such as intensity, color, orientation and motion. The
Guangtao Zhai +3 more
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Sensitivities in parameter estimation
IEEE Transactions on Automatic Control, 1981The method of equivalent observation [1] is extended to vector-valued constant parameters and to uncorrelated measurement noise sequences. It is then used to determine easily calculated partial derivatives of final covariances with respect to parameter variances.
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Existence and uniqueness of risk-sensitive estimates
IEEE Transactions on Automatic Control, 2002Risk-sensitive criteria have been used to derive robust filters, identifiers, and controllers. The fundamental issues of existence and uniqueness of an estimate of a random variable given a random vector with respect to an order-(/spl lambda/, p) risk-sensitive criterion are studied in this note.
James T. Lo, Thomas Wanner
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Estimating sensitivity and bias in a yes/no task
British Journal of Mathematical and Statistical Psychology, 2006The estimation of sensitivity and bias from data collected in a yes/no detectionâtheoretic experiment is complicated by the possibility of proportions of 0 or 1 appearing in the resulting contingency table. Inverse normal transforms of these probabilities result in mathematically intractable infinities.
Michael J, Hautus, Alan, Lee
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Denoising Monte Carlo sensitivity estimates
Operations Research Letters, 2012zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kang, W Kang, Wanmo +2 more
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Nonparametric estimation of probabilistic sensitivity measures
Statistics and Computing, 2019zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Antoniano-Villalobos Isadora +2 more
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Sensitivity analysis of grating parameter estimation
Applied Optics, 2002An optimization method for the sensitivity of diffraction efficiency measurements is presented. I define the sensitivity as the estimation precision of the grating parameters. The optimization method called sensitivity analysis for fitting scans all the possible measurement configurations and selects the configuration that yields the best sensitivity ...
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Simulation and sensitivity estimation
1996We will use the word simulation exclusively for the technique to mimic a random process on a computer. Since a computer is a deterministic machine, true randomness cannot be produced. Instead, one uses algorithms, which produce values which are (to a certain extent) indistinguishable from realizations of genuine random processes.
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Estimation of Sensitivity of Tubercle Bacilli to Cycloserine
Scandinavian Journal of Clinical and Laboratory Investigation, 1957(1957). Estimation of Sensitivity of Tubercle Bacilli to Cycloserine. Scandinavian Journal of Clinical and Laboratory Investigation: Vol. 9, No. 3, pp. 255-257.
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