The UU-test for statistical modeling of unimodal data

Adolfsson, 2019, To cluster, or not to cluster: an analysis of clusterability methods, Pattern Recognit., 88, 13, 10.1016/j.patcog.2018.10.026 Kalogeratos, 2012, Dip-means: an incremental clustering method for estimating the number of clusters, 2393 Hartigan, 1985, The dip test of unimodality, Ann. Stat., 13, 70, 10.1214/aos/1176346577 Siffer, 2018, Are your data gathered?, 2210 Dodge, 2008, Kolmogorov–Smirnov test, 283 Anderson, 1952, Asymptotic theory of certain “goodness of fit” criteria based on stochastic processes, Ann. Math. Statist., 23, 193, 10.1214/aoms/1177729437 Shapiro, 1965, An analysis of variance test for normality (complete samples), Biometrika, 52, 591, 10.1093/biomet/52.3-4.591 Silverman, 1981, Using kernel density estimates to investigate multimodality, J. R. Stat. Soc., 43, 97 Hall, 2001, On the calibration of Silverman’s test for multimodality, Stat. Sin., 515 Muller, 1991, Excess mass estimates and tests for multimodality, J. Am. Stat. Assoc., 86, 738 Hartigan, 1992, The runt test for multimodality, J. Classif., 9, 63, 10.1007/BF02618468 Rozál, 1994, The map test for multimodality, J. Classif., 11, 5, 10.1007/BF01201021 Maurus, 2016, Skinny-dip: clustering in a sea of noise, 1055 Schelling, 2018, Diptransformation: enhancing the structure of a dataset and thereby improving clustering, 407 Schelling, 2020, Dataset-transformation: improving clustering by enhancing the structure with dipscaling and diptransformation, Knowl. Inf. Syst., 62, 457, 10.1007/s10115-019-01388-5 Krause, 2005, Multimodal Projection Pursuit Using the Dip Statistic Robertson, 1988 McLachlan, 2000 Craigmile, 1997, Parameter estimation for finite mixtures of uniform distributions, Commun. Stat.-Theory Methods, 26, 1981, 10.1080/03610929708832026 Bouguila, 2020 Chen, 2005, Seeking multi-thresholds directly from support vectors for image segmentation, Neurocomputing, 67, 335, 10.1016/j.neucom.2004.12.006 Dua, 2017 Fox, 2019 Kaggle, (https://www.kaggle.com). Chamalis, 2018, The projected dip-means clustering algorithm, 1 Sammut, 2011 Hastie, 2009 Jolliffe, 2002 Bishop, 2006 Roux, 2018, A comparative study of divisive and agglomerative hierarchical clustering algorithms, J. Classif., 35, 345, 10.1007/s00357-018-9259-9 Boley, 1998, Principal direction divisive partitioning, Data Min. Knowl. Discov., 2, 325, 10.1023/A:1009740529316 Hamerly, 2003, Learning the k in k-means, 281 Rosin, 2001, Unimodal thresholding, Pattern Recognit., 34, 2083, 10.1016/S0031-3203(00)00136-9 Coudray, 2010, Robust threshold estimation for images with unimodal histograms, Pattern Recognit. Lett., 31, 1010, 10.1016/j.patrec.2009.12.025 Ng, 2006, Automatic thresholding for defect detection, Pattern Recognit. Lett., 27, 1644, 10.1016/j.patrec.2006.03.009