M-estimation with incomplete and dependent multivariate data

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Frahm, Gabriel, et al. “M-Estimation With Incomplete and Dependent Multivariate Data”. Journal of Multivariate Analysis, vol. 176, 2020, p. 104569, https://doi.org/10.1016/j.jmva.2019.104569.
Frahm, G., Nordhausen, K., & Oja, H. (2020). M-estimation with incomplete and dependent multivariate data. Journal of Multivariate Analysis, 176, 104569. https://doi.org/10.1016/j.jmva.2019.104569
Frahm, Gabriel, Klaus Nordhausen, and Hannu Oja. “M-Estimation With Incomplete and Dependent Multivariate Data”. Journal of Multivariate Analysis 176 (2020): 104569. https://doi.org/10.1016/j.jmva.2019.104569.
Frahm G, Nordhausen K, Oja H. M-estimation with incomplete and dependent multivariate data. Journal of Multivariate Analysis. 2020;176:104569.
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Refrences Analysis
Category Category Repetition
Science: Mathematics: Probabilities. Mathematical statistics22
Science: Mathematics22
Science: Biology (General)10
Social Sciences: Economic theory. Demography: Economics as a science8
Social Sciences: Statistics5
Social Sciences: Commerce: Business5
Medicine: Medicine (General): Computer applications to medicine. Medical informatics5
Social Sciences: Commerce: Business: Accounting. Bookkeeping3
Social Sciences: Finance3
Science: Mathematics: Instruments and machines: Electronic computers. Computer science2
Philosophy. Psychology. Religion: Psychology2
Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry: Neurology. Diseases of the nervous system: Psychiatry1
The category Science: Mathematics: Probabilities. Mathematical statistics 22 is the most frequently represented among the references in this article. It primarily includes studies from The Annals of Statistics and Biometrika. The chart below illustrates the number of referenced publications per year.
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Citations
Title Journal Journal Categories Citations Publication Date
Robust neural networks with random weights based on generalized M-estimation and PLS for imperfect industrial data modeling Control Engineering Practice
  • Technology: Mechanical engineering and machinery
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
  • Technology: Mechanical engineering and machinery
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Technology: Engineering (General). Civil engineering (General)
 8 2020
Citations Analysis
Category Category Repetition
Technology: Mechanical engineering and machinery1
Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks1
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics1
Technology: Engineering (General). Civil engineering (General)1
The category Technology: Mechanical engineering and machinery 1 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Robust neural networks with random weights based on generalized M-estimation and PLS for imperfect industrial data modeling and was published in 2020. The most recent citation comes from a 2020 study titled Robust neural networks with random weights based on generalized M-estimation and PLS for imperfect industrial data modeling. This article reached its peak citation in 2020, with 1 citations. It has been cited in 1 different journals. Among related journals, the Control Engineering Practice cited this research the most, with 1 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year