Package: carfima
Type: Package
Title: Continuous-Time Fractionally Integrated ARMA Process for
        Irregularly Spaced Long-Memory Time Series Data
Version: 2.0.1
Authors@R: c(person("Hyungsuk","Tak",role="aut",email="hyungsuk.tak@gmail.com",comment=c(ORCID="0000-0003-0334-8742")),
             person("Henghsiu", "Tsai", role = "aut", email="henghsiu.tsai@gmail.com"),
             person("Kisung", "You", role = c("aut", "cre"),email = "kyou@nd.edu",comment=c(ORCID="0000-0002-8584-459X")))
Description: We provide a toolbox to fit a continuous-time fractionally integrated ARMA process (CARFIMA) on univariate and irregularly spaced time series data via frequentist or Bayesian machinery. A general-order CARFIMA(p, H, q) model for p>q is specified in Tsai and Chan (2005) <doi:10.1111/j.1467-9868.2005.00522.x> and it involves (p+q+2) unknown model parameters, i.e., p AR parameters, q MA parameters, Hurst parameter H, and process uncertainty (standard deviation) sigma. The package produces their maximum likelihood estimates and asymptotic uncertainties using a global optimizer called the differential evolution algorithm. It also produces their posterior distributions via Metropolis within a Gibbs sampler equipped with adaptive Markov chain Monte Carlo for posterior sampling. These fitting procedures, however, may produce numerical errors if p>2. The toolbox also contains a function to simulate discrete time series data from CARFIMA(p, H, q) process given the model parameters and observation times.
License: GPL-2
Encoding: UTF-8
Imports: Rcpp, DEoptim, Rdpack, MASS, cubature, numDeriv, stats, utils,
        truncnorm, invgamma
LinkingTo: Rcpp, RcppArmadillo, cubature
RoxygenNote: 6.1.1
RdMacros: Rdpack
NeedsCompilation: yes
Packaged: 2019-01-23 00:37:05 UTC; kisung
Author: Hyungsuk Tak [aut] (<https://orcid.org/0000-0003-0334-8742>),
  Henghsiu Tsai [aut],
  Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)
Maintainer: Kisung You <kyou@nd.edu>
Repository: CRAN
Date/Publication: 2019-01-23 06:00:03 UTC
