LAUSR

In some sampling situations, the survey can result in an estimate of zero when it is known that the parameter being estimated is close to, but not equal to, zero. Examples include searching for rare animals or plants where the species is known to exist but all sample units failed to detect any activity. One way to deal with this is to ignore these zero estimates. Here we propose an estimator for sampling where we know the parameter of interest is not zero. Our proposed non-zero estimator will improve estimation and it can be more efficient than conventional estimators.