The following pages link to The random Tukey depth (Q1023863):
Displaying 26 items.
- Estimating the probability that a given vector is in the convex hull of a random sample (Q2689428) (← links)
- Resampling-based Classification Using Depth for Functional Curves (Q2828715) (← links)
- Different perspectives on object oriented data analysis (Q2922173) (← links)
- Integrated depth for functional data: statistical properties and consistency (Q2954227) (← links)
- Helly’s theorem: New variations and applications (Q2979647) (← links)
- A New Method for Ordering Functional Data and its Application to Diagnostic Test (Q3300628) (← links)
- Approximating Tukey's Depth (Q4431284) (← links)
- <i>DD</i>-Classifier: Nonparametric Classification Procedure Based on<i>DD</i>-Plot (Q4916509) (← links)
- Multivariate Functional Halfspace Depth (Q4975360) (← links)
- Combining dependent tests based on data depth with applications to the two-sample problem for data of arbitrary types (Q5030940) (← links)
- <i>β</i>-Skeleton depth functions and medians (Q5031701) (← links)
- Sparse Functional Boxplots for Multivariate Curves (Q5057222) (← links)
- Tukey Depths and Hamilton--Jacobi Differential Equations (Q5075722) (← links)
- A new approach for the computation of halfspace depth in high dimensions (Q5086196) (← links)
- Functional boxplots based on epigraphs and hypographs (Q5138060) (← links)
- (Q5501289) (← links)
- Tukey’s Depth for Object Data (Q6077569) (← links)
- Supervised classification of curves via a combined use of functional data analysis and tree-based methods (Q6104427) (← links)
- Nonparametric Fusion Learning for Multiparameters: Synthesize Inferences From Diverse Sources Using Data Depth and Confidence Distribution (Q6110722) (← links)
- A fast epigraph and hypograph-based approach for clustering functional data (Q6171766) (← links)
- Model-based statistical depth with applications to functional data (Q6536879) (← links)
- Symmetrisation of a class of two-sample tests by mutually considering depth ranks including functional spaces (Q6595789) (← links)
- A Decomposition of Total Variation Depth for Understanding Functional Outliers (Q6621655) (← links)
- Robust functional multivariate analysis of variance with environmental applications (Q6626368) (← links)
- Depthgram: visualizing outliers in high-dimensional functional data with application to fMRI data exploration (Q6628342) (← links)
- Pooling random forest and functional data analysis for biomedical signals supervised classification: theory and application to electrocardiogram data (Q6628360) (← links)
