View source: R/quasi_sym_equ.R

quasi_sym_equ | R Documentation |

Recursively compute the denominator of the individual conditional likelihood function for the Modified Quadratic Exponential Model recursively, adapted from Krailo & Pike (1984).

quasi_sym_equ(eta,s,y0=NULL)

`eta` |
individual vector of products between covariate and parameters |

`s` |
total score of the individual |

`y0` |
Individual initial observation for dynamic models |

`f` |
value of the denominator |

`d1` |
first derivative of the recursive function |

`dl1` |
a component of the score function |

`D2` |
second derivative of the recursive function |

`Dl2` |
a component of the Hessian matrix |

Francesco Bartolucci (University of Perugia), Claudia Pigini (University of Ancona "Politecnica delle Marche"), Francesco Valentini (University of Ancona "Politecnica delle Marche")

Bartolucci, F. and Nigro, V. (2010), A dynamic model for binary panel data with unobserved heterogeneity admitting a root-n consistent conditional estimator, *Econometrica*, **78**, 719-733.

Bartolucci, F., Nigro, V., & Pigini, C. (2018). Testing for state dependence in binary panel data with individual covariates by a modified quadratic exponential model. *Econometric Reviews*, **37(1)**, 61-88.

Bartolucci, F., Valentini. F., & Pigini, C. (2021), Recursive Computation of the Conditional Probability Function of the Quadratic Exponential Model for Binary Panel Data, *Computational Economics*, https://doi.org/10.1007/s10614-021-10218-2.

Krailo, M. D., & Pike, M. C. (1984). Algorithm AS 196: conditional multivariate logistic analysis of stratified case-control studies, *Journal of the Royal Statistical Society. Series C (Applied Statistics)*, **33(1)**, 95-103.

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