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Returns the approximating Gaussian model. This function is rarely needed itself, and is mainly available for testing and debugging purposes.
gaussian_approx(model, max_iter, conv_tol, ...)# S3 method for nongaussian gaussian_approx(model, max_iter = 100, conv_tol = 1e-08, ...)# S3 method for ssm_nlg gaussian_approx(model, max_iter = 100, conv_tol = 1e-08, iekf_iter = 0, ...)
# S3 method for nongaussian gaussian_approx(model, max_iter = 100, conv_tol = 1e-08, ...)
# S3 method for ssm_nlg gaussian_approx(model, max_iter = 100, conv_tol = 1e-08, iekf_iter = 0, ...)
Model to be approximated.
Maximum number of iterations.
Tolerance parameter.
Ignored.
For non-linear models, number of iterations in iterated EKF (defaults to 0).
# NOT RUN { data("poisson_series") model <- bsm_ng(y = poisson_series, sd_slope = 0.01, sd_level = 0.1, distribution = "poisson") out <- gaussian_approx(model) # }
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