Description Usage Arguments Details Value Note References See Also Examples

This function estimates the covariance matrix of the ML estimators of the
*β* parameters, using the asymptotic distribution and properties of the ML estimators.

1 | ```
VARbeta.fun(covariates, lambdafit)
``` |

`covariates` |
Matrix of covariates (each column is a covariate). |

`lambdafit` |
Numeric vector, the fitted PP intensity |

The covariance matrix is calculated as the inverse of the negative of the hessian matrix. The inverse of the matrix
is calculated using the solve function. If this function leads to an error in the calculation, the
inverse is calculated via its Cholesky decomposition. If this option also fails,
the covariance matrix is not estimated and a matrix of dimension *0 \times 0* is returned.

`VARbeta ` |
Coariance matrix of the |

The function `fitPP.fun`

calls this function.

Casella, G. and Berger, R.L., (2002). *Statistical inference.* Brooks/Cole.

Cebrian, A.C., Abaurrea, J. and Asin, J. (2015). NHPoisson: An R Package for
Fitting and Validating Nonhomogeneous Poisson Processes.
*Journal of Statistical Software*, 64(6), 1-24.

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