Results 1 to 10 of about 2,425,653 (248)
A Method of Accuracy Increment Using Segmented Regression
Algorithms, 2022 The main purpose of mathematical model building while employing statistical data analysis is to obtain high accuracy of approximation within the range of observed data and sufficient predictive properties.
Jamil Al-Azzeh +4 more
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Consistent model selection in segmented line regression [PDF]
Journal of Statistical Planning and Inference, 2016 The Schwarz criterion or Bayes Information Criterion (BIC) is often used to select a model dimension, and some variations of the BIC have been proposed in the context of change-point problems. In this paper, we consider a segmented line regression model with an unknown number of change-points and study asymptotic properties of Schwarz type criteria in ...
Hyune-Ju Kim, Jeankyung Kim
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The Log Likelihood Ratio in Segmented Regression
Annals of Statistics, 1975 This paper deals with the asymptotic distribution of the log likelihood ratio statistic in regression models which have different analytical forms in different regions of the domain of the independent variable. It is shown that under suitable identifiability conditions, the asymptotic chi square results of Wilks and Chernoff are applicable. It is shown
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Frontiers in Pharmacology, 2020 BackgroundIrrational use of antimicrobial agents for gastrointestinal diseases deserves attention, but corresponding antimicrobial stewardship programs (ASPs) are generally not a priority for managers.
Yaling Du +10 more
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Optimal Segmented Linear Regression for Financial Time Series Segmentation [PDF]
2021 International Conference on Data Mining Workshops (ICDMW), 2021 Given a financial time series data, one of the most fundamental and interesting challenges is the need to learn the stock dynamics signals in a financial time series data. A good example is to represent the time series in line segments which is often used as a pre-processing step for learning marketing signal patterns in financial computing.
Chi-Jen Wu, Wei-Sheng Zeng, Jan-Ming Ho
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Clustering-Based Segmented Regression for Particulate Matter Sensor Calibration
Applied Sciences, 2022 Nowadays, sensor-based air pollution sensing systems are widely deployed for fine-grained pollution monitoring. In-field calibration plays an important role in maintaining sensory data quality.
Sijie Liu, Xinyu Liu, Pei Lu
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Multiatlas Segmentation as Nonparametric Regression [PDF]
IEEE Transactions on Medical Imaging, 2014 This paper proposes a novel theoretical framework to model and analyze the statistical characteristics of a wide range of segmentation methods that incorporate a database of label maps or atlases; such methods are termed as label fusion or multiatlas segmentation.
Suyash P. Awate, Ross T. Whitaker
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 The Urban Agglomerations of Middle and Lower Reaches of the Yangtze River Economic Belt (UAMLYREB) have experienced rapid and intense urbanization over the past decades with natural ecosystems being converted to impervious surfaces.
Zhihui Li, Lu Peng, Feng Wu
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International Journal of Public Health, 2022 Objective: Social distancing has been confirmed to reduce the incidence of not only the COVID-19, but also the incidence of other diseases. Therefore, this study aimed to investigate the effect of social distancing policies on the incidence of infectious
Woo-Ri Lee +6 more
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Multiple change point analysis of hepatitis B reports in Xinjiang, China from 2006 to 2021
Frontiers in Public Health, 2023 ObjectiveHepatitis B (HB) is a major global challenge, but there has been a lack of epidemiological studies on HB incidence in Xinjiang from a change-point perspective.
Liping Yang +7 more
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