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  2. Bibliometrix - Wikipedia

    en.wikipedia.org/wiki/Bibliometrix

    Bibliometrix is a package for the R statistical programming language for quantitative research in scientometrics and bibliometrics. [1]Bibliometrics is the application of quantitative analysis and statistics to publications such as journal articles and their accompanying citation counts.

  3. Tidyverse - Wikipedia

    en.wikipedia.org/wiki/Tidyverse

    Characteristic features of tidyverse packages include extensive use of non-standard evaluation and encouraging piping. [3] [4] [5] As of November 2018, the tidyverse package and some of its individual packages comprise 5 out of the top 10 most downloaded R packages. [6] The tidyverse is the subject of multiple books and papers.

  4. Comparison of linear algebra libraries - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_linear...

    Free 3-clause BSD: Numerical linear algebra library with long history librsb: Michele Martone C, Fortran, M4 2011 1.2.0 / 09.2016 Free GPL: High-performance multi-threaded primitives for large sparse matrices. Support operations for iterative solvers: multiplication, triangular solve, scaling, matrix I/O, matrix rendering.

  5. Vectorization (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Vectorization_(mathematics)

    In Python NumPy arrays implement the flatten method, [note 1] while in R the desired effect can be achieved via the c() or as.vector() functions. In R, function vec() of package 'ks' allows vectorization and function vech() implemented in both packages 'ks' and 'sn' allows half-vectorization. [2] [3] [4]

  6. List of numerical libraries - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical_libraries

    De facto standard for matrix/tensor operations in Python. Pandas, a library for data manipulation and analysis. SageMath is a large mathematical software application which integrates the work of nearly 100 free software projects and supports linear algebra, combinatorics, numerical mathematics, calculus, and more. [16]

  7. Matrix-free methods - Wikipedia

    en.wikipedia.org/wiki/Matrix-free_methods

    Matrix-free conjugate gradient method has been applied in the non-linear elasto-plastic finite element solver. [7] Solving these equations requires the calculation of the Jacobian which is costly in terms of CPU time and storage. To avoid this expense, matrix-free methods are employed.

  8. Matrix completion - Wikipedia

    en.wikipedia.org/wiki/Matrix_completion

    In statistical learning point of view, the matrix completion problem is an application of matrix regularization which is a generalization of vector regularization. For example, in the low-rank matrix completion problem one may apply the regularization penalty taking the form of a nuclear norm R ( X ) = λ ‖ X ‖ ∗ {\displaystyle R(X ...

  9. R (programming language) - Wikipedia

    en.wikipedia.org/wiki/R_(programming_language)

    R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.