Estimates semiparametric highdimensional statespace models. Here we presume that both the observation and state distributions have Gaussian noise, but we let the observation equation evolve as an additive model in the state. In particular, we expand the state in the spline basis and estimate the coefficients via the group lasso. As this model is nonlinear, we use the LaplaceGaussian filter to estimate the hidden states quickly and accurately.
Package details 


Maintainer  
License  GPL 
Version  0.1 
URL  http://github.iu.edu/dajmcdon/spasm 
Package repository  View on GitHub 
Installation 
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