Optimal combination of sampled measurements
AssigneeAT&T Intellectual Property II, L.P.
InventorsNicholas G. Duffield, Carsten Lund, Mikkel Thorup
Life of this patent
Estimating the term…
Abstract
Two regularized estimators that avoid the pathologies associated with variance estimation are disclosed. The regularized variance estimator adds a contribution to estimated variance representing the likely error, and hence ameliorates the pathologies of estimating small variances while at the same time allowing more reliable estimates to be balanced in the convex combination estimator. The bounded variance estimator employs an upper bound to the variance which avoids estimation pathologies when sampling probabilities are very small.
Claims20
A method of estimating an attribute of objects, comprising:
- obtaining a first sample of the objects based on a first sampling distribution;
- obtaining a first estimate of the attribute based on the first sample;
- obtaining a second sample of the objects based on a second sampling distribution, where the second sampling distribution is different from the first sampling distribution;
- obtaining a second estimate of the attribute based on the second sample;
- determining a bound for a variance based upon each of the first sample and the second sample;
- and
- combining the first sample and the second sample using a variance value for each one of the first sample and the second sample that is equal to or larger than the bound for the variance for the first sample and second sample.
A computer readable medium containing stored instructions which when executed on a computer causes the computer to perform a method comprising:
- obtaining a first sample of the objects based on a first sampling distribution;
- obtaining a first estimate of the attribute based on the first sample;
- obtaining a second sample of the objects based on a second sampling distribution, where the second sampling distribution is different from the first sampling distribution;
- obtaining a second estimate of the attribute based on the second sample;
- determining a bound for a variance based upon each of the first sample and the second sample;
- and
- combining the first sample and the second sample using a variance value for each one of the first sample and the second sample that is equal to or larger than the bound for the variance for the first sample and second sample.
Dependencies are inferred from the claim text.