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A Regression Model for Market Segmentation Studies
Journal of Marketing Research, 1980A model is developed for incorporating the long-standing marketing research effort of explaining variation in observed consumption behavior into the more recent notion that such behavior has an inherent component of randomness. The model recognizes that consumption behavior on any given occasion will fluctuate around some mean consumption level and ...
Albert R. Wildt, John M. Mccann
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Realistic Predictors for Regression and Semantic Segmentation
2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA), 2023Krishna Chaitanya Gadepally +3 more
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Boundary Regression for Human Vertebrae Segmentation
2019 9th International Conference on Advances in Computing and Communication (ICACC), 2019The diagnosis and treatment of pathologies like Low back pain, Osteoporosis, Spondyflolisthesis etc. require detailed analysis of spinal images. Manual segmentation of vertebrae in spinal images is difficult. In this paper we discuss an automatic method for segmentation of vertebrae.
M.A Ancy Brigit +2 more
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Optimal segmentation of signals in a linear regression framework
[Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing, 1991The problem of estimating the time instants when the dynamical properties of a signal make abrupt changes is studied. This segmentation problem is usually considered as exponential in time. The author presents a specific but natural signal mode-called a changing regression model-and points out a method to compute an optimal estimate of the segmentation
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Sparse regressions for joint segmentation and linear prediction
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014Regularizing the least-squares criterion with the total number of coefficient changes, it is possible to estimate time-varying (TV) autoregressive (AR) models with piecewise-constant coefficients. Such models emerge in various applications including speech segmentation using linear predictors.
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Spontaneous Regression of Segmental Arterial Mediolysis
Journal of Vascular and Interventional Radiology, 2020Pupulim LF, Terraz S
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Segmented Cox Regression (60 Patients)
2012Cox regression assesses time to events, like death or cure, and the effects of predictors like comorbidity and frailty. If a predictor is not significant, then time-dependent Cox regression may be a relevant approach. It assesses whether the predictor interacts with time. Time dependent Cox has been explained in Chap. 56.
Ton J. Cleophas, Aeilko H. Zwinderman
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A segmentation approach to regression problems with switching-points
2023 14th International Conference on Information and Communication Technology Convergence (ICTC), 2023Shao-Tung Chang, Kang-Ping Lu
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Regression Segmentation for M³ Spinal Images.
IEEE transactions on medical imaging, 2016Clinical routine often requires to analyze spinal images of multiple anatomic structures in multiple anatomic planes from multiple imaging modalities (M(3)). Unfortunately, existing methods for segmenting spinal images are still limited to one specific structure, in one specific plane or from one specific modality (S(3)).
Zhijie, Wang +5 more
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Low-cost carriers and tourism in the Italian regions: A segmented regression model
Annals of Tourism Research, 2022Anna Serena Vergori, Serena Arima
exaly