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The group of packages strives to provide a cohesive collection of functions to deal with common data science tasks, including data import, cleaning, transformation and visualisation (notably with the ggplot2 package). The R Infrastructure packages [31] support coding and the development of R packages and as of 2021-05-04, Metacran [17] lists 16 ...
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]
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.
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.
R package for phylogenetic assembly R, two‐stage Bayesian inference using MrBayes 3.2 Thomas et al. 2013 [31] PAUP* Phylogenetic analysis using parsimony (*and other methods) Maximum parsimony, distance matrix, maximum likelihood: D. Swofford phangorn [32] Phylogenetic analysis in R: ML, MP, distance matrix, bootstrap, phylogentic networks ...
The Python package NumPy provides a pseudoinverse calculation through its functions matrix.I and linalg.pinv; its pinv uses the SVD-based algorithm. SciPy adds a function scipy.linalg.pinv that uses a least-squares solver. The MASS package for R provides a calculation of the Moore–Penrose inverse through the ginv function. [24]
The term R-matrix has several meanings, depending on the field of study.. The term R-matrix is used in connection with the Yang–Baxter equation, first introduced in the field of statistical mechanics in the works of J. B. McGuire in 1964 [1] and C. N. Yang in 1967 [2] and in the group algebra [] of the symmetric group in the work of A. A. Jucys in 1966.
The high rank matrix completion in general is NP-Hard. However, with certain assumptions, some incomplete high rank matrix or even full rank matrix can be completed. Eriksson, Balzano and Nowak [10] have considered the problem of completing a matrix with the assumption that the columns of the matrix belong to a union of multiple low-rank subspaces.