Cluster detection of spatial regression coefficients.
Sign Up to like & getrecommendations! Published in 2017 at "Statistics in medicine"
DOI: 10.1002/sim.7172
Abstract: Popular approaches to spatial cluster detection, such as the spatial scan statistic, are defined in terms of the responses. Here, we consider a varying-coefficient regression and spatial clusters in the regression coefficients. For varying-coefficient regression,… read more here.
Keywords: cluster detection; methodology; regression coefficients; regression ... See more keywords
A Semantic Transferred Priori for Hyperspectral Target Detection With Spatial–Spectral Association
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3261302
Abstract: Hyperspectral target detection is a crucial application that encompasses military, environmental, and civil needs. Target detection algorithms that have prior knowledge often assume a fixed laboratory target spectrum, which can differ significantly from the test… read more here.
Keywords: hyperspectral target; target spectrum; target detection; detection ... See more keywords
Outlier detection in spatial error models using modified thresholding-based iterative procedure for outlier detection approach
Sign Up to like & getrecommendations! Published in 2024 at "BMC Medical Research Methodology"
DOI: 10.1186/s12874-024-02208-3
Abstract: Background Outliers, data points that significantly deviate from the norm, can have a substantial impact on statistical inference and provide valuable insights in data analysis. Multiple methods have been developed for outlier detection, however, almost… read more here.
Keywords: detection; methodology; method; outlier detection ... See more keywords