other · Code Ocean · 2019

Autoregressive Model Parameter Estimation

Cagatay Candan

Cited by 0Open access

Abstract

Autoregressive Model Parameter Estimation An implementation of the suggested method for the autoregressive (AR) modeling of WSS random processes. The method aims to find the maximum likelihood estimate for the model parameters. Yet, the exact maximum likelihood solution is infeasible to implement in many cases and the suggested aims to provide a good approximation to the maximum likelihood solution. The provided MATLAB code makes a comparison of the likelihood value attained by the suggested method and different methods, including the method of brute force numerical search by the MATLAB's optimization routines.

Cite this paper

APA 7

Candan, C. (2019). Autoregressive Model Parameter Estimation. Code Ocean. https://doi.org/10.24433/co.0721956.v1

MLA 9

Candan, Cagatay. “Autoregressive Model Parameter Estimation.” Code Ocean, 2019, https://doi.org/10.24433/co.0721956.v1.

Chicago

Candan, Cagatay. 2019. “Autoregressive Model Parameter Estimation.” Code Ocean. https://doi.org/10.24433/co.0721956.v1.

Harvard

Candan, C. (2019) ‘Autoregressive Model Parameter Estimation’, Code Ocean. Available at: https://doi.org/10.24433/co.0721956.v1.

BibTeX

@misc{candan2019autoregressive,
  title = {{Autoregressive Model Parameter Estimation}},
  author = {Candan, Cagatay},
  journal = {Code Ocean},
  year = {2019},
  doi = {10.24433/co.0721956.v1}
}

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