Detecting and removing outlier(s) in electromyographic gait-related patterns

In this paper, we propose a method for outlier detection and removal in electromyographic gait-related patterns (EMG-GRPs). The goal was to detect and remove EMG-GRPs that reduce the quality of gait data while preserving natural biological variations in EMG-GRPs. The proposed procedure consists of general statistical tests and is simple to use. The Friedman test with multiple comparisons was used to find particular EMG-GRPs that are extremely different from others. Next, outlying observations were calculated for each suspected stride waveform by applying the generalized extreme studentized deviate test. To complete the analysis, we applied different outlier criteria. The results suggest that an EMG-GRP is an outlier if it differs from at least 50% of the other stride waveforms and contains at least 20% of the outlying observations. The EMG signal remains a realistic representation of muscle activity and demonstrates step-by-step variability once the outliers, as defined here, are removed.     

SPECULATIVE ATTACKS AND THE INFORMATION ROLE OF THE INTEREST RATE

This paper models currency attacks as carried out by speculators who condition their actions on private signals about the state and on the market‐clearing interest rate. Besides affecting speculators' payoffs, this interest rate also provides an endogenous public signal. For a plausible type of investment strategies, the dual role of the interest rate allows the model to explain abrupt and intense speculative attacks solely via economic fundamentals, without resorting to sunspot variables. This result underlies a novel policy implication: An official intervention in the foreign exchange market may reinforce a currency peg by influencing the precision of public information. (JEL: D82, D84, F31)