dobj.dxt.tomogravity: Analytic gradient of objective function of Zhang et al. 2003
In networkTomography: Tools for network tomography

Requires bounded optimization to maintain positive OD flows, and only those flows that are not deterministically zero should be included in the estimation.

1	dobj.dxt.tomogravity(xt, yt, A, srcDstInd, lambda)

`xt`	length-k numeric vector of point-to-point flows
`yt`	length-m numeric vector of observed aggregate flows
`A`	m x k routing matrix, yt = A xt
`srcDstInd`	list of source and destination flow indices corresponding to each point-to-point flow, as produced by `getSrcDstIndices`
`lambda`	regularization parameter for mutual information prior. Note that this is scaled by the squared total traffic in the objective function before scaling the mututal information prior.