Results 251 to 260 of about 449,237 (302)

Feedback Control for Binary Response

2017 Conference on Technologies and Applications of Artificial Intelligence (TAAI), 2017
Defect rate control is crucial in industries. When binary response is considered, the defect rate is the average of these binary responses. In this study, with logistic regression model and sparsity assumption, the feedback control problem is expressed as an optimization problem which solves a hinge loss with an L1 penalty. Here the hinge loss function
Ping-Yang Chen, Chi-Chun Hsia, Yen-Hao Su, Ray-Bing Chen, Sheng-Mao Chang   +4 more
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Testing for Independence of Binary Responses

Biometrical Journal, 1986
AbstractIn the context of experiments involving visual inspection of random dot patterns the problem of testing the null hypothesis of independence of binary responses is considered. A flexible model for dependence between binary responses is proposed. Two tests, optimal under different versions of the model, are derived.
FIDLER, [No Value], DEJONGE, AB
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Power of Tests in Binary Response Models [PDF]

Econometrica, 1999
Most hypotheses in binary response models are composite. The null hypothesis is usually that one or more slope coefficients are zero. Typically, the sequence of alternatives of interest is one in which the slope coefficients are increasing in absolute value.
Wurtz, Allan; id_orcid 0009-0007-0080-7284, Savin, Gene   +1 more
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Network and covariate adjusted response‐adaptive design for binary response

Statistics in Medicine, 2023
Randomization is a distinguishing feature of clinical trials for unbiased assessment of treatment efficacy. With a growing demand for more flexible and efficient randomization schemes and motivated by the idea of adaptive design, in this article we propose the network and covariate adjusted response‐adaptive (NCARA) design that can concurrently manage ...
Hao Mei, Jiaxin Xie, Yichen Qin, Yang Li
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Response shrinkage estimators in binary regression

Computational Statistics & Data Analysis, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gerhard Tutz 0001, Florian Leitenstorfer
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Binary and Graded Responses in Gene Networks

Science Signaling, 2002
Although gene expression can be regulated in a graded or a binary fashion, the majority of eukaryotic genes are either fully activated or not expressed at all in individual cells. This binary response might be an inherent property of many eukaryotic promoters. Analysis of transcription under the control of yeast GAL1
Louis, Matthieu, Becskei, Attila
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Binary response data

2009
Abstract Much social science data consist of categorical variables. Familiar examples are religion, nationality, residence (urban/rural), type of dwelling, level of education and social class. The categories may be unordered (religion, nationality) or ordered (degree of disablement, attitude to a social question).
Murray Aitkin, Brian Francis, John Hinde, Ross Darnell   +3 more
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Theorems on Binary Responses to Combinations of Stimuli

Biometrical Journal, 1992
AbstractBinary responses, such as dead or alive, in response to two or more stimuli are considered in this paper. Their joint actions are defined to be either independent, conditionally independent, additive, synergistic or antagonistic. The Bernoulli parameter is replaced by a dose‐response function. Theorems on the probability of a response resulting
J. Wanzer Drane, Chongyau Fu, Tiberiu Postelnicu, Prof. J. Wanzer Drane, Chongyau Fu, Tiberiu Postelnicu   +5 more
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Regression models for binary longitudinal responses

Statistics and Computing, 1998
Some conditional models to deal with binary longitudinal responses are proposed, extending random effects models to include serial dependence of Markovian form, and hence allowing for quite general association structures between repeated observations recorded on the same individual.
AITKIN M. A., ALFO', Marco
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A Robust Design of a Screen for a Binary Response

Biometrika, 1992
Summary: Optimal screening procedures are derived using Bayesian decision theory. A simple heuristic solution is determined using an asymptotic posterior distribution for the parameters in a linear probit model. The solution is shown to be optimal within a class of possible procedures and robust to departures from model assumptions.
Boys, R. J., Glazebrook, K. D.
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