Simulation-Based Quasi-Likelihood Estimation
We provide a method for parameter estimation of parametric statistical models which can be at least simulated and where standard methods, such as maximum likelihood, least squares or Bayesian algorithms (including MCMC) are not applicable. We follow the quasi-likelihood theory to estimate the unknown model parameter by finding a root of the so-called quasi-score estimating function. For an overview of our method and further in-depth examples please see the vignette.
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