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Estimation theory is used to develop a model of a human decision maker in a self-paced, visual data smoothing task. The model is basically a noisy fixed-point smoother combined with a weighting function that discounts data in relation to its distance (in time) from the point being smoothed. Experimental data is used to estimate the parameters of the model. Applications of the model to the design of information displays and man-computer interactive decision making systems are considered.