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This work presents a model reduction algorithm motivated by a connection between frequency-domain projection methods and approximation of truncated balanced realizations. The method is computationally simple to implement, has near-optimal error properties, and possesses simple error estimation and order-control procedures. Usage of the method also enables straightforward exploitation of information about the particular application and setting, as well as circuit functional information, such as frequency weighting information and correlations between network port waveforms. When such specific information is available, standard truncated balanced realization algorithms generate models far from optimal according to statistical decision criteria. Examples are shown to demonstrate that the method can outperform the standard order reduction techniques by providing similar accuracy with lower order models or superior accuracy for the same size model.