Numerical Standard Errors Computation in R

Collection of functions designed to calculate numerical standard error (NSE) of univariate time series as described in Ardia et al. (2018) and Ardia and Bluteau (2017) .

nse

Computation of numerical standard errors in R

nse (Ardia and Bluteau, 2017) is an R package for computing the numerical standard error (NSE), an estimate of the standard deviation of a simulation result, if the simulation experiment were to be repeated many times. The package provides a set of wrappers around several R packages, which give access to more than thirty NSE estimators, including batch means estimators, initial sequence estimators, spectrum at zero estimators, heteroskedasticity and autocorrelation consistent (HAC) kernel estimators and bootstrap estimators. See Ardia and Bluteau (2017) for details. The full set of methods available in nse is summarized in Ardia et al. (2018) together with several examples of applications in econometrics and finance.

The latest stable version of nse is available at https://cran.r-project.org/package=nse.

The latest development version of nse is available at https://github.com/keblu/nse.

Please cite the package in publications!

By using nse you agree to the following rules:

1. You must cite Ardia et al. (2018) in working papers and published papers that use nse.
2. You must place the following URL in a footnote to help others find nse: https://CRAN.R-project.org/package=nse.
3. You assume all risk for the use of nse.

Ardia, D., Bluteau, K., Hoogerheide, L.F. (2018).
Methods for computing numerical standard errors: Review and application to Value-at-Risk estimation.
Journal of Time Series Econometrics 10(2) pp 1-9.
https://doi.org/10.1515/jtse-2017-0011 https://doi.org/10.2139/ssrn.2741587

Ardia, D., Bluteau, K. (2017).
nse: Computation of numerical standard errors in R.
Journal of Open Source Software 10(2).
https://doi.org/10.21105/joss.00172