  Although there are a few works reported in the literature considering loss
tomography in the general topology, there is few well established result since
all of them rely either on simulations or on experiments that have many random
factors affecting the outcome. To improve the situation, we address a number of
issues in this paper that include a maximum likelihood estimator (MLE) for the
general topology, the statistical properties of the MLE, the statistical
properties of a frequently referred estimator called the moving variance and
weighted average (MVWA), and a renewed MVWA that removes the restriction of
knowing variance in advance from the MVWA. The statistical properties covers
minimum-variance unbiasedness, efficiency, and variances of the estimates
obtained by the estimators. Given the properties, we can evaluate the
estimators without the need of simulations. To verify the properties, a
simulation study is conducted that confirms the accuracy of the findings.
