Melvin J. Hinich’s research while affiliated with University of Texas at Austin and other places

This paper considers the origin and implications of higher-order (non-linear) cumulant spectral signatures generated by a hypoid gear assembly in a light utility van. This analysis demonstrates that the hypoid gear silencing problem is qualitatively and quantitatively different than the problems in gear design, both nominal and detailed, in particular: • The production of sound by final drive gear trains is an extremely inefficient process; therefore, the vibration components which dominate sound generation are negligible quantities in typical gear design trade-offs. The usual silencing adjustments often shift but do not remove the offending source. • Human hearing is acutely sensitive to the phase-coherent sinusoidal oscillations with modulated sidebands produced by hypoid gear trains. Modifications which reduce signature energy in a specific narrow band component may have no useful effect on perceived acoustic annoyance. • Final drive measurements capture transient, stochastically modulated hypoid gear signatures confounded by highly correlated, non-Gaussian interference. Experimental design to explicitly measure the transient drive signals and the sources of correlated inference is essential for useful results. • Emerging higher-order spectral analysis methods require long measurement ensembles to achieve appropriate resolution bandwidth and statistical convergence. Efficient data handling architecture for long, replicated ensembles is a pragmatic necessity.

Two American political scientists and a Ukrainian sociologist analyze the results of Ukraine's 1998 parliamentary elections. The purpose is to test propositions about the cognitive organization of voters' attitudes about issues and evaluations of the political parties that seek to mobilize their vote. The article then examines differences on these scores between the East and West of the country. A test is provided of the spatial model of voting that has been found to be a successful predictor of belief organization in other countries and milieux.

EEG and field potential rhythms established in the cortex and thalamus may accommodate the propagation of seizures. This article describes the interaction between thalamus and cortex during pentylenetetrazol (PTZ) seizures in rats with and without prior treatment with ethosuximide (ESM), a well-known antiepileptic drug (AED) that raises the threshold for seizures, was given before PTZ. The AED was given before PTZ convulsant administration. We track this thalamo-cortical association with a novel measure we have called the cross-bicoherence gain, or BISCOH. This quantity allows us to measure the spectral coherence in a purely higher order spectralmethodology. BISCOH is able to track the formation of nonlinearities at specific frequencies in the recorded EEG. BISCOH showed a strong increase in low alpha wave harmonic generationat 10 and 12.5 Hz after ESM treatment (p < 0.02 and p < 0.007, respectively). Conventional coherence failed to show distinctive and significant changes in thalamo-cortical coupling after ESM treatment at those frequencies and instead showed changes at 5 Hz. This rise in cortical rhythms is evidence of harmonic generation or new frequency formation in the thalamo-cortical system withAED therapy. BISCOH could become a powerful tool in unraveling changes in coherence due to neuroelectric modulation resulting from drug treatment or electrical stimulation.

The purpose of this article is to present a statistical uncertainty principle that can be used when localizing a single change in the mean of a band-limited stationary random process. The statistical model investigated is a continuous time process that experiences a shift in its mean. This continuous time process is presumed to be sampled using an ideal low-pass filter. The least squares estimate of the location of the change in mean is asymptotically Gaussian. The standard deviation of the least squares estimate of the location of the change-point provides a physical limit to the accuracy of the estimate of the time of the mean shift which cannot be bettered.

This paper investigates the duration dependence of the US stock market cycles. A new classification method for bull and bear market regimes based on the crossing of the market index and its moving average is proposed. We show evidence of duration dependence in whole cycles. The half cycles, however, are found to be duration independent. More importantly, we find that the degree of duration dependence of the US stock market cycles has dropped after the launch of the NASDAQ index.

In 2008, both Barack Obama and John McCain repeatedly talked about “reform” and “change” on the campaign trail, presumably believing that voters would respond to a president who could challenge the established way of doing business. The authors gauge the significance of “reform” politics in 2008 through two analyses. First, they estimate a two-dimensional issue space, paying particular attention to the possibility of a reform/establishment dimension. Second, they consider whether voters (1) preferred reform candidates, and (2) saw Obama or McCain as credible reform candidates. The data indicate the existence of a reform–establishment dimension. However, neither Obama nor McCain effectively convinced voters that they were reformers.

We use a new statistical test based on the signal coherence function to detect subtle periodicities in the Chilean exchange rate. We resort to a unique intraday data set that allows us to capture persistent cyclical movements during the day that challenge the random walk hypothesis. We provide a microstructural explanation for the observed behavior, and also look at the day-of-the-week effect for the Chilean peso and find that the different days of the week indeed have different behavior patterns. This is an important result for investment allocation and risk assessment.

In this article, we show how tests of nonlinear serial dependence can be applied to high-frequency time series data that exhibit high volatility, strong mean reversion, and leptokurtotis. Portmanteau correlation, bicorrelation, and tricorrelation tests are used to detect nonlinear serial dependence in the data. Trimming is used to control for the presence of outliers in the data. The data that are employed are 161,786 half-hourly spot electricity price observations recorded over nearly a decade in the wholesale electricity market in New South Wales, Australia. Strong evidence of nonlinear serial dependence is found and its implications for time series modeling are discussed.