Description Usage Arguments Value References See Also

Computes gradient of Q-function with respect to log(c(lambda,phi)) for EM algorithm from Cao et al. (2000) for their locally IID model.

1 |

`logtheta` |
numeric vector (length k+1) of log(lambda) (1:k) and log(phi) (last entry) |

`c` |
power parameter in model of Cao et al. (2000) |

`M` |
matrix (n x k) of conditional expectations for OD flows, one time per row |

`rdiag` |
numeric vector (length k) containing diagonal of conditional covariance matrix R |

`epsilon` |
numeric nugget to add to diagonal of covariance for numerical stability |

numeric vector of same length as logtheta containing calculated gradient

J. Cao, D. Davis, S. Van Der Viel, and B. Yu. Time-varying network tomography: router link data. Journal of the American Statistical Association, 95:1063-75, 2000.

Other CaoEtAl: `Q_iid`

;
`Q_smoothed`

; `R_estep`

;
`grad_smoothed`

; `locally_iid_EM`

;
`m_estep`

; `phi_init`

;
`smoothed_EM`

networkTomography documentation built on May 29, 2017, 4:56 p.m.

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