Efficient estimation of the link function parameter in a robust Bayesian binary regression model

2014 ◽  
Vol 73 ◽  
pp. 87-102 ◽  
Author(s):  
Vivekananda Roy
1991 ◽  
Vol 19 (2) ◽  
pp. 165-178 ◽  
Author(s):  
P. E. Greenwood ◽  
W. Wefelmeyer

Author(s):  
Robert D. McMichael ◽  
Sean M. Blakley ◽  
Sergey Dushenko

Optbayesexpt is a public domain, open-source python package that provides adaptive algorithms for efficient estimation/measurement of parameters in a model function. Parameter estimation is the type of measurement one would conventionally tackle with a sequence of data acquisition steps followed by fitting. The software is designed to provide data-based control of experiments, effectively learning from incoming measurement results and using that information to select future measurement settings live and online as measurements progress. The settings are chosen to have the best chances of improving the measurement results. With these methods optbayesexpt is designed to increase the efficiency of a sequence of measurements, yielding better results and/or lower cost. In a recent experiment, optbayesexpt yielded an order of magnitude increase in speed for measurement of a few narrow peaks in a broad spectral range.


Test ◽  
2020 ◽  
Vol 29 (4) ◽  
pp. 1051-1071
Author(s):  
Guilherme Pumi ◽  
Cristine Rauber ◽  
Fábio M. Bayer

2020 ◽  
Vol 10 (4) ◽  
pp. 1657-1673
Author(s):  
Aliyah Glover ◽  
Lakshmi Pillai ◽  
Shannon Doerhoff ◽  
Tuhin Virmani

Background: Freezing of gait (FOG) is a debilitating feature of Parkinson’s disease (PD) for which treatments are limited. To develop neuroprotective strategies, determining whether disease progression is different in phenotypic variants of PD is essential. Objective: To determine if freezers have a faster decline in spatiotemporal gait parameters. Methods: Subjects were enrolled in a longitudinal study and assessed every 3– 6 months. Continuous gait in the levodopa ON-state was collected using a gait mat (Protokinetics). The slope of change/year in spatiotemporal gait parameters was calculated. Results: 26 freezers, 31 non-freezers, and 25 controls completed an average of 6 visits over 28 months. Freezers had a faster decline in mean stride-length, stride-velocity, swing-%, single-support-%, and variability in single-support-% compared to non-freezers (p < 0.05). Gait decline was not correlated with initial levodopa dose, duration of levodopa therapy, change in levodopa dose or change in Montreal Cognitive Assessment scores (p > 0.25). Gait progression parameters were required to obtain 95% accuracy in categorizing freezers and non-freezers groups in a forward step-wise binary regression model. Change in mean stride-length, mean stride-width, and swing-% variability along with initial foot-length variability, mean swing-% and apathy scores were significant variables in the model. Conclusion: Freezers had a faster temporal decline in objectively quantified gait, and inclusion of longitudinal gait changes in a binary regression model greatly increased categorization accuracy. Levodopa dosing, cognitive decline and disease severity were not significant in our model. Early detection of this differential decline may help define freezing prone groups for testing putative treatments.


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