Approaches to Bayesian Smooth Unimodal Regression
نویسنده
چکیده
George Woodworth Dec 13, 1999 (Draft please send comments to [email protected]) 1. Background Speech Articulation Data The data in Figure 1 were obtained by asking 51 subjects ranging in age from 8 to 73 years to track, using jaw movements alone, a dot moving sinusoidally in one dimension at .6 Hz on a video monitor. Their jaw movements were captured electronically by means of strain guages and translated into the motion of a cursor which was to track (follow) the moving dot. Fidelity of tracking was measured in several ways, including TTD, the RMS difference between target and tracker shown in Figure 1. Low values of TTD indicate that the subject has high control of the speech articulator ((lips, jaw, or voice). The investigators believed ability to control speech articulators to be unimodal in age, reaching a broad optimum in early to middle adulthood. Hence, they wished to fit unimodal regressions to such data. The purpose was to establish agenorms against which to compare the performance of neurologically compromised individuals.
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