Patent ID: 8352215

Claim:
A distributed data processor system having multiple data processors for generating an updated least squares estimate (b) for a parameter to be estimated (β) using an iteratively reweighted least squares technique on a scenario defined by a design matrix (X), a response variable vector (Y), and the parameter to be estimated (β), the system comprising: a root data processor for performing a plurality of processing iterations, wherein the updated least squares estimate (b) is calculated by the root data processor during each processing iteration; the root data processor being configured to command further processing iterations by node data processors until the updated least squares estimate (b) converges; and the node data processors for receiving the plurality of processing iteration commands from the root data processor, upon receipt of a command to perform a processing iteration, each node data processor being further configured to: receive one or more rows of the design matrix (X) assigned to the each node data processor and one or more rows of the response variable vector (Y) assigned to the each node data processor; update values of a weight matrix (W) for rows according to a current state of the updated least squares estimate (b) for processing iterations subsequent to a first processing iteration; determine a first intermediate value based on the assigned rows of the design matrix (X) and the weight matrix (W); determine a second intermediate value based on the assigned rows of the design matrix (X), the assigned rows of the response variable vector (Y), and the updated values of the weight matrix (W); output the first intermediate value and the second intermediate value to the root data processor; the root data processor being configured to receive the first intermediate values and the second intermediate values from the node data processors and to calculate the updated least squares estimate (b) based on a sum of the first intermediate values from the node data processors and a sum of the second intermediate values from the node data processors; the root data processor being configured to store the updated least squares estimate (b) on a non-transitory computer-readable medium as the parameter to be estimated (β) upon convergence of the updated least squares estimate (b).