Internal function. Finds the posterior mean and covariance at the observation times `tobs`

, for every subject; see Section 2 of the referenced article for further details.

1 | ```
posteriorobs(Sigma0inv, sigma, muprior, Xtilda, tobs, YI)
``` |

`Sigma0inv` |
Prior precision matrix at the observation times |

`sigma` |
Infinitessimal standard deviation of the tied-down Brownian motion in the prior. |

`muprior` |
Prior mean at the observation times |

`Xtilda` |
An n by N matrix with columns given by the values of |

`tobs` |
Row vector of n observation times (in increasing order, same for each subject). |

`YI` |
An N times (n-1) matrix with rows given by the values of |

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