1. An attribute modeler method implemented in a general purpose computer, said method comprising: providing for an initialization step that provides for a likelihood function, a first order prior function; a calibration data set; providing a flexible interface in which the likelihood function, the first order first order prior function, and the second order prior function are written in a programming language; providing for parameter bounding in which parameters determined to be too large are sequentially locked down based on assigned priorities, such that one parameter is locked down at a time and the system remodeled to determining the effect on other parameters; providing for outlier flagging in which anomalous elements in the said calibration data set are identified by calculating the force that the outlier is exerting on the model using the gradient of the likelihood function; providing for Output comprising forces, confidence intervals, and other factors that are unique to this modeler and useful in refining the model.