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tsprass

DCCA:Detrended Fluctuation and Detrended Cross-Correlation Analysis

A collection of functions to perform Detrended Fluctuation Analysis (DFA) and Detrended Cross-Correlation Analysis (DCCA). This package implements the results presented in Prass, T.S. and Pumi, G. (2019). "On the behavior of the DFA and DCCA in trend-stationary processes" <arXiv:1910.10589>.

Maintained by Taiane Schaedler Prass. Last updated 5 years ago.

fortran openblas

2.48 score 6 scripts 1 dependents

cran

seedCCA:Seeded Canonical Correlation Analysis

Functions for dimension reduction through the seeded canonical correlation analysis are provided. A classical canonical correlation analysis (CCA) is one of useful statistical methods in multivariate data analysis, but it is limited in use due to the matrix inversion for large p small n data. To overcome this, a seeded CCA has been proposed in Im, Gang and Yoo (2015) \doi{10.1002/cem.2691}. The seeded CCA is a two-step procedure. The sets of variables are initially reduced by successively projecting cov(X,Y) or cov(Y,X) onto cov(X) and cov(Y), respectively, without loss of information on canonical correlation analysis, following Cook, Li and Chiaromonte (2007) \doi{10.1093/biomet/asm038} and Lee and Yoo (2014) \doi{10.1111/anzs.12057}. Then, the canonical correlation is finalized with the initially-reduced two sets of variables.

Maintained by Jae Keun Yoo. Last updated 3 years ago.

1.00 score