IDEAS home Printed from https://ideas.repec.org/a/eee/agisys/v199y2022ics0308521x22000427.html
   My bibliography  Save this article

The potential of kernel density estimation for modelling relations among dairy farm characteristics

Author

Listed:
  • Senga Kiessé, Tristan
  • Corson, Michael S.
  • Eugène, Maguy

Abstract

Agricultural systems are generally characterised by many dependent variables that represent their management practices and performances. Parametric approaches are usually used to explore data collected from farms and relations among variables. However, these approaches are generally limited by strong assumptions about the shape of the model that relates variables to each other, which can induce bias in studies.

Suggested Citation

  • Senga Kiessé, Tristan & Corson, Michael S. & Eugène, Maguy, 2022. "The potential of kernel density estimation for modelling relations among dairy farm characteristics," Agricultural Systems, Elsevier, vol. 199(C).
    • Handle: RePEc:eee:agisys:v:199:y:2022:i:c:s0308521x22000427
    DOI: 10.1016/j.agsy.2022.103406
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308521X22000427
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agsy.2022.103406?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. Casey, J.W. & Holden, N.M., 2005. "Analysis of greenhouse gas emissions from the average Irish milk production system," Agricultural Systems, Elsevier, vol. 86(1), pages 97-114, October.
    2. Tarn Duong & Martin L. Hazelton, 2005. "Cross‐validation Bandwidth Matrices for Multivariate Kernel Density Estimation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 32(3), pages 485-506, September.
    3. Christopher A. Wolf & Daniel A. Sumner, 2001. "Are Farm Size Distributions Bimodal? Evidence from Kernel Density Estimates of Dairy Farm Size Distributions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(1), pages 77-88.
    4. Chen, Song Xi, 1999. "Beta kernel estimators for density functions," Computational Statistics & Data Analysis, Elsevier, vol. 31(2), pages 131-145, August.
    5. Duong, Tarn, 2007. "ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 21(i07).
    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. R. N. Rattihalli & S. B. Patil, 2021. "Data Dependent Asymmetric Kernels for Estimating the Density Function," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 155-186, February.
    2. Pulkkinen, Seppo, 2015. "Ridge-based method for finding curvilinear structures from noisy data," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 89-109.
    3. Karim M Abadir & Michel Lubrano, 2023. "Explicit solutions for the asymptotically-optimal bandwidth in cross validation," AMSE Working Papers 2336, Aix-Marseille School of Economics, France.
    4. Zougab, Nabil & Adjabi, Smail & Kokonendji, Célestin C., 2014. "Bayesian estimation of adaptive bandwidth matrices in multivariate kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 28-38.
    5. Schoch, Tobias & Staub, Kaspar & Pfister, Christian, 2012. "Social inequality and the biological standard of living: An anthropometric analysis of Swiss conscription data, 1875–1950," Economics & Human Biology, Elsevier, vol. 10(2), pages 154-173.
    6. Hirukawa, Masayuki, 2010. "Nonparametric multiplicative bias correction for kernel-type density estimation on the unit interval," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 473-495, February.
    7. Hu, Shuowen & Poskitt, D.S. & Zhang, Xibin, 2012. "Bayesian adaptive bandwidth kernel density estimation of irregular multivariate distributions," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 732-740.
    8. Ouimet, Frédéric & Tolosana-Delgado, Raimon, 2022. "Asymptotic properties of Dirichlet kernel density estimators," Journal of Multivariate Analysis, Elsevier, vol. 187(C).
    9. Bouezmarni, Taoufik & Van Bellegem, Sébastien, 2009. "Nonparametric Beta Kernel Estimator for Long Memory Time Series," IDEI Working Papers 633, Institut d'Économie Industrielle (IDEI), Toulouse.
    10. Hagmann, M. & Scaillet, O., 2007. "Local multiplicative bias correction for asymmetric kernel density estimators," Journal of Econometrics, Elsevier, vol. 141(1), pages 213-249, November.
    11. Billings, Stephen B. & Johnson, Erik B., 2012. "A non-parametric test for industrial specialization," Journal of Urban Economics, Elsevier, vol. 71(3), pages 312-331.
    12. Fernandes, Marcelo & Grammig, Joachim, 2005. "Nonparametric specification tests for conditional duration models," Journal of Econometrics, Elsevier, vol. 127(1), pages 35-68, July.
    13. Boris Branisa & Adriana Cardozo, 2009. "Regional Growth Convergence in Colombia Using Social Indicators," Ibero America Institute for Econ. Research (IAI) Discussion Papers 195, Ibero-America Institute for Economic Research.
    14. Nikolay Gospodinov & Masayuki Hirukawa, 2008. "Time Series Nonparametric Regression Using Asymmetric Kernels with an Application to Estimation of Scalar Diffusion Processes," CIRJE F-Series CIRJE-F-573, CIRJE, Faculty of Economics, University of Tokyo.
    15. Salvatore D. Tomarchio & Antonio Punzo, 2019. "Modelling the loss given default distribution via a family of zero‐and‐one inflated mixture models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(4), pages 1247-1266, October.
    16. Hoffman, Eric & Cavigelli, Michel A. & Camargo, Gustavo & Ryan, Matthew & Ackroyd, Victoria J. & Richard, Tom L. & Mirsky, Steven, 2018. "Energy use and greenhouse gas emissions in organic and conventional grain crop production: Accounting for nutrient inflows," Agricultural Systems, Elsevier, vol. 162(C), pages 89-96.
    17. Grammig, Joachim G. & Peter, Franziska J., 2008. "International price discovery in the presence of market microstructure effects," CFR Working Papers 08-10, University of Cologne, Centre for Financial Research (CFR).
    18. Suqin Ge & João Macieira, 2024. "Unobserved Worker Quality and Inter‐Industry Wage Differentials," Journal of Industrial Economics, Wiley Blackwell, vol. 72(1), pages 459-515, March.
    19. Malý, M. & Hálová, P. & Havlíková, M. & Žáková-Kroupová, Z., 2017. "Valuation of Public Goods: The Case of Emissions from Livestock Holdings in the Czech Republic," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 9(1), March.
    20. Tauer, Loren W. & Mishra, Ashok K., 2006. "Can the small dairy farm remain competitive in US agriculture?," Food Policy, Elsevier, vol. 31(5), pages 458-468, October.

    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:eee:agisys:v:199:y:2022:i:c:s0308521x22000427. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agsy .

    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.