a r t i c l e i n f o JEL classification: C32 C51 L94 Q40 Keywords: Wholesale spot electricity price markets Constant and dynamic conditional correlation Multivariate GARCH This paper examines the interrelationships of wholesale spot electricity prices among the four regional A multivariate generalised autoregressive conditional heteroscedasticity model with time-varying correlations. Dynamic c...

The purpose was to study correlations amongst IMRT DVH evaluation points and how their relaxation impacts the overall plan. 100 head-and-neck cancer cases, using the Eclipse treatment planning system with the same protocol, are statisti-cally analyzed for PTV, brainstem, and spinal cord. To measure variations amongst the plans, we use (i) interquartile range (IQR) of volume as a function of dos...

This paper considers structure learning of ferromagnetic Ising models Markov on sparse ErdősRényi random graphs with constant average degree c > 0. We propose simple, local and robust algorithms and analyze their performances in the regime of correlation decay, i.e., when c tanhJmax < 1 (where Jmax is the maximum inverse temperature in the model). The algorithms are robust because (i) they do n...

Correlations between U.S. stocks and the aggregate U.S. market are much greater for downside moves, especially for extreme downside moves, than for upside moves. We develop a new statistic for measuring, comparing, and testing asymmetries in conditional correlations. Conditional on the downside, correlations in the data differ from the conditional correlations implied by a normal distribution b...

Quantile regression (QR) fits a linear model for conditional quantiles, just as ordinary least squares (OLS) fits a linear model for conditional means. An attractive feature of OLS is that it gives the minimum mean square error linear approximation to the conditional expectation function even when the linear model is misspecified. Empirical research using quantile regression with discrete covar...

Although market interdependence would seem to be conceptually straightforward, being based on international fundamentals, there are no generally accepted testing strategies. This paper tests for the sensitivity of the empirical results reported in Veiga and McAleer (2004), who use the vector autoregressive moving average asymmetric generalised autoregressive conditional heteroskedasticity (VARM...

A common statistical problem is the testing of independence of two (response) variables conditionally on a third (control) variable. In the first part of this paper, we extend Hoeffding’s concept of estimability of degree r to testability of degree r, and show that independence is testable of degree two, while conditional independence is not testable of any degree if the control variable is con...

The equations of motion for the nth order velocity differences raise the interest in correlation functions containing both large and small scales simultaneously. We consider the scaling of such objects and also their conditional average representation with emphasis on the question of whether they behave differently in the inertial or the viscous subranges. The turbulent flow data are obtained b...

Traditionally, insights into neural computation have been furnished by averaged firing rates from many stimulus repetitions or trials. We pursue an analysis of neural response variance to unveil neural computations that cannot be discerned from measures of average firing rate. We analyzed single-neuron recordings from the lateral intraparietal area (LIP), during a perceptual decision-making tas...