1. A method, comprising: acquiring measurement data from one or more semiconductor wafers of a processed first lot, the data comprising a plurality of contexts; applying a model comprising parameters with partitioning along the contexts to the measurement data; and applying a constraint on a subset of the model parameters such that the subset remains centered around zero to provide consistent updates for automated process control of lots processed after the first lot, wherein applying the model comprises applying a model of the form 
 y k =mu k +h k x k +w k to the measurement data, in which y k comprises the measurement data, h k comprises a row vector of 1s and 0s with 1s being assigned to the active context values, x k comprises a vector of all possible bias values, w k comprises noise, m comprises the known process gain, u k comprises the recipe settings used to process the lot, and k comprises the lot run counter, wherein a solution for the parameter estimates, x k , is postulated in the form of recursive updates, and wherein applying a constraint comprises applying a constraint of the form 
 0=βx k , in which β comprises a matrix of context terms with 1s being assigned to constrained terms and 0s being assigned to unconstrained terms.