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Fast and efficient computation of rolling and expanding eigenanalysis for time-series data.

R 27.36% C++ 71.54% C 1.10%

rolleigen's Introduction

rolleigen

Overview

rolleigen is a package that provides analytical computation of rolling and expanding eigenanalysis for time-series data.

Installation

Install the development version from GitHub:

# install.packages("devtools")
devtools::install_github("jasonjfoster/rolleigen") # roll (>= 1.1.7)

Usage

Load the package and supply a dataset:

library(rolleigen)

n <- 15
m <- 3
x <- matrix(rnorm(n * m), nrow = n, ncol = m)
y <- rnorm(n)
weights <- 0.9 ^ (n:1)

Then, to compute rolling and expanding eigenvalues and eigenvectors, use the roll_eigen function:

# rolling eigenvalues and eigenvectors with complete windows
roll_eigen(x, width = 5)

# rolling eigenvalues and eigenvectors with partial windows
roll_eigen(x, width = 5, min_obs = 1)

# expanding eigenvalues and eigenvectors with partial windows
roll_eigen(x, width = n, min_obs = 1)

# expanding eigenvalues and eigenvectors with partial windows and weights
roll_eigen(x, width = n, min_obs = 1, weights = weights)

Or use the roll_pcr function to compute rolling and expanding principal component regressions:

# rolling regressions with complete windows
roll_pcr(x, y, width = 5, n_comps = 1)

# rolling regressions with partial windows
roll_pcr(x, y, width = 5, n_comps = 1, min_obs = 1)

# expanding regressions with partial windows
roll_pcr(x, y, width = n, n_comps = 1, min_obs = 1)

# expanding regressions with partial windows and weights
roll_pcr(x, y, width = n, n_comps = 1, min_obs = 1, weights = weights)