IDEAS home Printed from https://ideas.repec.org/p/zbw/caseps/200426.html
   My bibliography  Save this paper

Transforms in Statistics

Author

Listed:
  • Vidakovic, Brani

Abstract

It is not an overstatement to say that statistics is based on various transformations of data. Basic statistical summaries such as the sample mean, variance, z-scores, histograms, etc., are all transformed data. Some more advanced summaries, such as principal components, periodograms, empirical characteristic functions, etc., are also examples of transformed data. To give a just coverage of transforms utilized in statistics will take a size of a monograph. In this chapter we will focus only on several important transforms with the emphasis on novel multiscale transforms (wavelet transforms and its relatives).

Suggested Citation

  • Vidakovic, Brani, 2004. "Transforms in Statistics," Papers 2004,26, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    • Handle: RePEc:zbw:caseps:200426
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/22199/1/26_bv.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. A. Antoniadis, 1997. "Wavelets in statistics: A review," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 6(2), pages 97-130, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601.

    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. Emmanouil Androulakis & Christos Koukouvinos & Kalliopi Mylona & Filia Vonta, 2010. "A real survival analysis application via variable selection methods for Cox's proportional hazards model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(8), pages 1399-1406.
    2. E. Androulakis & C. Koukouvinos, 2013. "A new variable selection method for uniform designs," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(12), pages 2564-2578, December.
    3. Canhong Wen & Xueqin Wang & Shaoli Wang, 2015. "Laplace Error Penalty-based Variable Selection in High Dimension," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(3), pages 685-700, September.
    4. A. Karagrigoriou & C. Koukouvinos & K. Mylona, 2010. "On the advantages of the non-concave penalized likelihood model selection method with minimum prediction errors in large-scale medical studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(1), pages 13-24.
    5. Chesneau, Christophe & Dewan, Isha & Doosti, Hassan, 2016. "Nonparametric estimation of a quantile density function by wavelet methods," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 161-174.
    6. Xingwei Tong & Xin He & Liuquan Sun & Jianguo Sun, 2009. "Variable Selection for Panel Count Data via Non‐Concave Penalized Estimating Function," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(4), pages 620-635, December.
    7. E. Androulakis & C. Koukouvinos & F. Vonta, 2014. "Tuning parameter selection in penalized generalized linear models for discrete data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(4), pages 276-292, November.
    8. Ertefaie Ashkan & Asgharian Masoud & Stephens David A., 2018. "Variable Selection in Causal Inference using a Simultaneous Penalization Method," Journal of Causal Inference, De Gruyter, vol. 6(1), pages 1-16, March.
    9. Christophe Chesneau & Fabien Navarro, 2017. "On the pointwise mean squared error of a multidimensional term-by-term thresholding wavelet estimator," Working Papers 2017-68, Center for Research in Economics and Statistics.
    10. Aminghafari, Mina & Cheze, Nathalie & Poggi, Jean-Michel, 2006. "Multivariate denoising using wavelets and principal component analysis," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2381-2398, May.
    11. Abbaszadeh, Mohammad & Chesneau, Christophe & Doosti, Hassan, 2012. "Nonparametric estimation of density under bias and multiplicative censoring via wavelet methods," Statistics & Probability Letters, Elsevier, vol. 82(5), pages 932-941.
    12. Felix Abramovich & Claudia Angelini & Daniela Canditiis, 2007. "Pointwise optimality of Bayesian wavelet estimators," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 59(3), pages 425-434, September.
    13. Jianqing Fan & Jinchi Lv, 2010. "Comments on: ℓ 1 -penalization for mixture regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(2), pages 264-269, August.
    14. Bulla, Ingo & Chesneau, Christophe & Navarro, Fabien & Mark, Tanya, 2015. "A note on the adaptive estimation of a bi-dimensional density in the case of knowledge of the copula density," Statistics & Probability Letters, Elsevier, vol. 105(C), pages 6-13.
    15. Liu-Cang Wu & Zhong-Zhan Zhang & Deng-Ke Xu, 2012. "Variable selection in joint mean and variance models of Box--Cox transformation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(12), pages 2543-2555, August.
    16. Yao Dong & He Jiang, 2018. "A Two-Stage Regularization Method for Variable Selection and Forecasting in High-Order Interaction Model," Complexity, Hindawi, vol. 2018, pages 1-12, November.
    17. Chalise, Prabhakar & Fridley, Brooke L., 2012. "Comparison of penalty functions for sparse canonical correlation analysis," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 245-254.
    18. Christophe Chesneau & Jalal Fadili, 2012. "Adaptive wavelet estimation of a function in an indirect regression model," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(1), pages 25-46, January.
    19. Christophe Chesneau, 2014. "A Note on Wavelet Estimation of the Derivatives of a Regression Function in a Random Design Setting," International Journal of Mathematics and Mathematical Sciences, Hindawi, vol. 2014, pages 1-8, April.
    20. Abhik Ghosh & Magne Thoresen, 2018. "Non-concave penalization in linear mixed-effect models and regularized selection of fixed effects," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(2), pages 179-210, April.

    More about this item

    Statistics

    Access and download statistics

    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:zbw:caseps:200426. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/cahubde.html .

    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.