MONOCAR (multivariate overlapping noisy observation continuous-time autoregression) is a continuous-time model of time-series data. MONOCAR is aimed at addressing several common complications with time-series data:
These features exist in a wide range of time-series data. Two common types of data in political science that include most or all of these features are polling data and events data.
More details on the MONOCAR model, these data complications, and how that model addresses them can be found in the following article:
Tahk, Alexander M. 2015. “A Continuous-Time, Latent-Variable Model of Time-Series Data.” Political Analysis 23 (Spring): 278–298.
The article is available here.
CARMAgeddon is an R package that performs estimation and inference of MONOCAR models. Other continuous-time models may be added to the package in the future. Documentation for the package and examples of its use can be found here. The command to estimate a MONOCAR model is
The package can be compiled from source code or installed from a binary package for OS X or Windows. Use of the package requires R, a free software environment for statistical computing and graphics that can be downloaded here. The package also depends on the R packages Rcpp, RcppArmadillo, RcppParallel, and nloptr. All of these packages are available from CRAN.
Users running OS X or Windows can install CARMAgeddon by running
install.packages("CARMAgeddon", repos="http://r.tahk.us/") from an R prompt.
Alternatively, binary packages can be downloaded for OS X here or for Windows here.
Installation of CARMAgeddon from the source package requires a C++ compiler as well as the R packages mentioned above. Once the prerequisites are installed, the CARMAgeddon package can be installed by running
install.packages("CARMAgeddon", repos="http://r.tahk.us/", type="source")
Alternatively, the source package can be downloaded here.
The CARMAgeddon package was written by Alexander Tahk. For questions about MONOCAR or the CARMAgeddon package, please email the author. Contact information can be found here.