fda.usc

fda.usc: Functional Data Analysis and Utilities for Statistical Computing. Routines for exploratory and descriptive analysis of functional data such as depth measurements, atypical curves detection, regression models, supervised classification, unsupervised classification and functional analysis of variance.


References in zbMATH (referenced in 45 articles , 1 standard article )

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  1. Barinder Thind, Sidi Wu, Richard Groenewald, Jiguo Cao: FuncNN: An R Package to Fit Deep Neural Networks Using Generalized Input Spaces (2020) arXiv
  2. Dai, Wenlin; Mrkvička, Tomáš; Sun, Ying; Genton, Marc G.: Functional outlier detection and taxonomy by sequential transformations (2020)
  3. García-Portugués, Eduardo; Álvarez-Liébana, Javier; Álvarez-Pérez, Gonzalo; González-Manteiga, Wenceslao: Goodness-of-fit tests for functional linear models based on integrated projections (2020)
  4. Mrkvička, Tomáš; Myllymäki, Mari; Jílek, Milan; Hahn, Ute: A one-way ANOVA test for functional data with graphical interpretation. (2020)
  5. Blanquero, R.; Carrizosa, E.; Jiménez-Cordero, A.; Martín-Barragán, B.: Functional-bandwidth kernel for support vector machine with functional data: an alternating optimization algorithm (2019)
  6. Cuesta-Albertos, Juan A.; García-Portugués, Eduardo; Febrero-Bande, Manuel; González-Manteiga, Wenceslao: Goodness-of-fit tests for the functional linear model based on randomly projected empirical processes (2019)
  7. Febrero-Bande, Manuel; González-Manteiga, Wenceslao; Oviedo de la Fuente, Manuel: Variable selection in functional additive regression models (2019)
  8. Górecki, Tomasz; Smaga, Łukasz: fdANOVA: an R software package for analysis of variance for univariate and multivariate functional data (2019)
  9. Kosiorowski, Daniel; Rydlewski, Jerzy P.; Snarska, Małgorzata: Detecting a structural change in functional time series using local Wilcoxon statistic (2019)
  10. Oleksii Pokotylo; Pavlo Mozharovskyi; Rainer Dyckerhoff: Depth and Depth-Based Classification with R Package ddalpha (2019) not zbMATH
  11. Rivera-García, Diego; García-Escudero, Luis A.; Mayo-Iscar, Agustín; Ortega, Joaquín: Robust clustering for functional data based on trimming and constraints (2019)
  12. Slaoui, Yousri: Wild bootstrap bandwidth selection of recursive nonparametric relative regression for independent functional data (2019)
  13. Tekbudak, Merve Yasemin; Alfaro-Córdoba, Marcela; Maity, Arnab; Staicu, Ana-Maria: A comparison of testing methods in scalar-on-function regression (2019)
  14. Tian, Yahui; Gel, Yulia R.: Fusing data depth with complex networks: community detection with prior information (2019)
  15. Wang, Longbing; Cao, Ruiyuan; Du, Jiang; Zhang, Zhongzhan: A nonparametric inverse probability weighted estimation for functional data with missing response data at random (2019)
  16. Zambom, Adriano Zanin; Collazos, Julian A. A.; Dias, Ronaldo: Functional data clustering via hypothesis testing (k)-means (2019)
  17. Justel, Ana; Svarc, Marcela: A divisive clustering method for functional data with special consideration of outliers (2018)
  18. Kim, Hyojoong; Kim, Heeyoung: Functional logistic regression with fused Lasso penalty (2018)
  19. Mair, Patrick: Modern psychometrics with R (2018)
  20. Manrique, Tito; Crambes, Christophe; Hilgert, Nadine: Ridge regression for the functional concurrent model (2018)

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