Filter Methods for Parameter Estimation in Linear and Non Linear Regression Models

We present a method based on filtering algorithms to estimate the parameters of linear, i.e. the coefficients and the variance of the error term. The proposed algorithms make use of Particle Filters following Ristic, B., Arulampalam, S., Gordon, N. (2004, ISBN: 158053631X) resampling methods. Parameters of logistic regression models are also estimated using an evolutionary particle filter method.




  • Function PF_lm.R has changed the output, now it returns a list of three elements
  • Changes in the examples section of PF_lm.R documentation
  • Better performance achieved with the new function PF_lm_ss.R which uses the method of simple sampling as resampling method


  • Changes in the documentation

0.1.0 Initial Release

Reference manual

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0.1.3 by Christian Llano Robayo, 6 months ago

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Authors: Christian Llano Robayo [aut, cre] , Nazrul Shaikh [aut]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports MASS, stats

See at CRAN