A model for pricing data bundles based on minimax risks for estimation of a location parameter

Consider a situation involving many sources of finite-length data, with buyers potentially interested in purchasing data from any bundle (subset) of the sources. A principled way is presented to assign a price to each source, when the value of the data is measured in terms of how much information about an underlying location parameter can be extracted from it. Apart from the operational relevance to data pricing, these results also have relevance to sensor network theory.