IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v39y2024i3d10.1007_s00180-023-01382-0.html
   My bibliography  Save this article

hermiter: R package for sequential nonparametric estimation

Author

Listed:
  • Michael Stephanou

    (Rand Merchant Bank)

  • Melvin Varughese

    (University of Cape Town
    University of Western Australia)

Abstract

This article introduces the R package hermiter which facilitates estimation of univariate and bivariate probability density functions and cumulative distribution functions along with full quantile functions (univariate) and nonparametric correlation coefficients (bivariate) using Hermite series based estimators. The algorithms implemented in the hermiter package are particularly useful in the sequential setting (both stationary and non-stationary) and one-pass batch estimation setting for large data sets. In addition, the Hermite series based estimators are approximately mergeable allowing parallel and distributed estimation.

Suggested Citation

  • Michael Stephanou & Melvin Varughese, 2024. "hermiter: R package for sequential nonparametric estimation," Computational Statistics, Springer, vol. 39(3), pages 1127-1163, May.
    • Handle: RePEc:spr:compst:v:39:y:2024:i:3:d:10.1007_s00180-023-01382-0
    DOI: 10.1007/s00180-023-01382-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00180-023-01382-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00180-023-01382-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Michael Stephanou & Melvin Varughese, 2021. "On the properties of hermite series based distribution function estimators," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(4), pages 535-559, May.
    2. Christophe Croux & Catherine Dehon, 2010. "Influence functions of the Spearman and Kendall correlation measures," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(4), pages 497-515, November.
    3. Mildenberger, Thoralf & Weinert, Henrike, 2012. "The benchden Package: Benchmark Densities for Nonparametric Density Estimation," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 46(i14).
    4. Greblicki, Wlodzimierz & Pawlak, Miroslaw, 1985. "Pointwise consistency of the hermite series density estimate," Statistics & Probability Letters, Elsevier, vol. 3(2), pages 65-69, April.
    5. Greblicki, W?odzimierz & Pawlak, Miros?aw, 1984. "Hermite series estimates of a probability density and its derivatives," Journal of Multivariate Analysis, Elsevier, vol. 15(2), pages 174-182, October.
    6. E. Liebscher, 1990. "Hermite series estimators for probability densities," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 37(1), pages 321-343, December.
    7. Asma Jmaei & Yousri Slaoui & Wassima Dellagi, 2017. "Recursive distribution estimator defined by stochastic approximation method using Bernstein polynomials," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(4), pages 792-805, October.
    8. Stephanou, Michael & Varughese, Melvin, 2021. "Sequential estimation of Spearman rank correlation using Hermite series estimators," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
    9. Eddelbuettel, Dirk & Francois, Romain, 2011. "Rcpp: Seamless R and C++ Integration," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i08).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stephanou, Michael & Varughese, Melvin, 2021. "Sequential estimation of Spearman rank correlation using Hermite series estimators," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
    2. Michael Stephanou & Melvin Varughese, 2021. "On the properties of hermite series based distribution function estimators," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(4), pages 535-559, May.
    3. Foster, Joshua, 2022. "Semi-nonparametric estimation of secret reserve prices in auctions," Economics Letters, Elsevier, vol. 220(C).
    4. Claudio G. Borroni & D. Michele Cifarelli, 2017. "The influence function of Gini’s gamma," METRON, Springer;Sapienza Università di Roma, vol. 75(1), pages 17-29, April.
    5. Wilson J. Wright & Peter N. Neitlich & Alyssa E. Shiel & Mevin B. Hooten, 2022. "Mechanistic spatial models for heavy metal pollution," Environmetrics, John Wiley & Sons, Ltd., vol. 33(8), December.
    6. repec:plo:pcbi00:1005544 is not listed on IDEAS
    7. Michael Pfarrhofer, 2024. "Forecasts with Bayesian vector autoregressions under real time conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 771-801, April.
    8. Gijbels, Irène & Kika, Vojtěch & Omelka, Marek, 2021. "On the specification of multivariate association measures and their behaviour with increasing dimension," Journal of Multivariate Analysis, Elsevier, vol. 182(C).
    9. Choi, Insu & Kim, Woo Chang, 2025. "A multifaceted graph-wise network analysis of sector-based financial instruments’ price-based discrepancies with diverse statistical interdependencies," The North American Journal of Economics and Finance, Elsevier, vol. 75(PB).
    10. Frank Bodendorf & Manuel Lutz & Jörg Franke, 2021. "Valuation and pricing of software licenses to support supplier–buyer negotiations: A case study in the automotive industry," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(7), pages 1686-1702, October.
    11. Shen, Yunyi & Olson, Erik R. & Van Deelen, Timothy R., 2021. "Spatially explicit modeling of community occupancy using Markov Random Field models with imperfect observation: Mesocarnivores in Apostle Islands National Lakeshore," Ecological Modelling, Elsevier, vol. 459(C).
    12. Barati, Hojjat & Yazici, Anil & Almotahari, Amirmasoud, 2024. "A methodology for ranking of critical links in transportation networks based on criticality score distributions," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    13. Pablo Aragonés‐Beltrán & Mª. Carmen González‐Cruz & Astrid León‐Camargo & Rosario Viñoles‐Cebolla, 2023. "Assessment of regional development needs according to criteria based on the Sustainable Development Goals in the Meta Region (Colombia)," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(2), pages 1101-1121, April.
    14. Fernández de Marcos Giménez de los Galanes, Alberto & García Portugués, Eduardo, 2022. "Data-driven stabilizations of goodness-of-fit tests," DES - Working Papers. Statistics and Econometrics. WS 35324, Universidad Carlos III de Madrid. Departamento de Estadística.
    15. Bandara, Kanchana & Varpe, Øystein & Ji, Rubao & Eiane, Ketil, 2018. "A high-resolution modeling study on diel and seasonal vertical migrations of high-latitude copepods," Ecological Modelling, Elsevier, vol. 368(C), pages 357-376.
    16. Aparisi-Cerdá, I. & Ribó-Pérez, D. & Gomar-Pascual, J. & Pineda-Soler, J. & Poveda-Bautista, R. & García-Melón, M., 2024. "Assessing gender and climate objectives interactions in urban decarbonisation policies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    17. Carter Allen & Yuzhou Chang & Brian Neelon & Won Chang & Hang J. Kim & Zihai Li & Qin Ma & Dongjun Chung, 2023. "A Bayesian multivariate mixture model for high throughput spatial transcriptomics," Biometrics, The International Biometric Society, vol. 79(3), pages 1775-1787, September.
    18. Sloot Henrik, 2022. "Implementing Markovian models for extendible Marshall–Olkin distributions," Dependence Modeling, De Gruyter, vol. 10(1), pages 308-343, January.
    19. Cindy Frascolla & Guillaume Lecuelle & Pascal Schlich & Hervé Cardot, 2022. "Two sample tests for Semi-Markov processes with parametric sojourn time distributions: an application in sensory analysis," Computational Statistics, Springer, vol. 37(5), pages 2553-2580, November.
    20. Juan C. Laria & M. Carmen Aguilera-Morillo & Rosa E. Lillo, 2023. "Group linear algorithm with sparse principal decomposition: a variable selection and clustering method for generalized linear models," Statistical Papers, Springer, vol. 64(1), pages 227-253, February.
    21. Ghislain Geniaux, 2024. "Speeding up estimation of spatially varying coefficients models," Journal of Geographical Systems, Springer, vol. 26(3), pages 293-327, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:compst:v:39:y:2024:i:3:d:10.1007_s00180-023-01382-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.