ctsmTMB

Description

Perform state and parameter inference, and forecasting, in stochastic state-space systems using the 'ctsmTMB' class. This class, built with the 'R6' package, provides a user-friendly interface for defining and handling state-space models. Inference is based on maximum likelihood estimation, with derivatives efficiently computed through automatic differentiation enabled by the 'TMB'/'RTMB' packages (Kristensen et al., 2016) <doi:10.18637/jss.v070.i05>. The available inference methods include Kalman filters, in addition to a Laplace approximation-based smoothing method. For further details of these methods refer to the documentation of the 'CTSMR' package <https://ctsm.info/ctsmr-reference.pdf> and Thygesen (2025) <doi:10.48550/arXiv.2503.21358>. Forecasting capabilities include moment predictions and stochastic path simulations, both implemented in 'C++' using 'Rcpp' (Eddelbuettel et al., 2018) <doi:10.1080/00031305.2017.1375990> for computational efficiency.

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installed size is 22.5Mb
  sub-directories of 1Mb or more:
    doc    1.4Mb
    libs  20.4Mb

installed size is 22.7Mb
  sub-directories of 1Mb or more:
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installed size is 22.5Mb
  sub-directories of 1Mb or more:
    doc    1.4Mb
    libs  20.4Mb

installed size is 22.7Mb
  sub-directories of 1Mb or more:
    doc    1.4Mb
    libs  20.6Mb

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