Kuznetsov independence for interval-valued expectations and sets of probability distributions: Properties and algorithms

Kuznetsov independence of variables X and Y means that, for any pair of bounded functions f(X) and g(Y), E[f(X)g(Y)]=E[f(X)] *times* E[g(Y)], where E[.] denotes interval-valued expectation and *times* denotes interval multiplication. We present properties of Kuznetsov independence for several variables, and connect it with other concepts of independence in the literature; in particular we show that strong extensions are always included in sets of probability distributions whose lower and upper expectations satisfy Kuznetsov independence. We introduce an algorithm that computes lower expectations subject to judgments of Kuznetsov independence by mixing column generation techniques with nonlinear programming. Finally, we define a concept of conditional Kuznetsov independence, and study its graphoid properties.

Maximum likelihood estimation of higher-order integer-valued autoregressive processes

In this article, we extend the earlier work of Freeland and McCabe [Journal of time Series Analysis (2004) Vol. 25, pp. 701–722] and develop a general framework for maximum likelihood (ML) analysis of higher-order integer-valued autoregressive processes. Our exposition includes the case where the innovation sequence has a Poisson distribution and the thinning is binomial. A recursive representation of the transition probability of the model is proposed. Based on this transition probability, we derive expressions for the score function and the Fisher information matrix, which form the basis for ML estimation and inference. Similar to the results in Freeland and McCabe (2004), we show that the score function and the Fisher information matrix can be neatly represented as conditional expectations. Using the INAR(2) speci?cation with binomial thinning and Poisson innovations, we examine both the asymptotic e?ciency and ?nite sample properties of the ML estimator in relation to the widely used conditional least
squares (CLS) and Yule–Walker (YW) estimators. We conclude that, if the Poisson assumption can be justi?ed, there are substantial gains to be had from using ML especially when the thinning parameters are large.

Diving behaviour during the internesting interval for loggerhead turtles Caretta caretta nesting in Cyprus

Time depth recorders were used to assess the patterns of depth utilisation by 2 loggerhead turtles Caretta caretta in Cyprus, eastern Mediterranean. Dives to the seabed accounted for 59 % (171 h) and 75 % (215 h) of the internesting interval, respectively, with most dives being shallow (

Maximum likelihood estimation of higher-order integer-valued autoregressive processes

Corrigendum Vol. 30, Issue 2, 259, Article first published online: 15 MAR 2009 to correct the order of authors names: Bu R., K. Hadri, and B. McCabe.

Real-valued fixed-complexity sphere decoder for high dimensional QAM-MIMO systems

The development of high performance, low computational complexity detection algorithms is a key challenge for real-time Multiple-Input Multiple-Output (MIMO) communication system design. The Fixed-Complexity Sphere Decoder (FSD) algorithm is one of the most promising approaches, enabling quasi-ML decoding accuracy and high performance implementation due to its deterministic, highly parallel structure. However, it suffers from exponential growth in computational complexity as the number of MIMO transmit antennas increases, critically limiting its scalability to larger MIMO system topologies. In this paper, we present a solution to this problem by applying a novel cutting protocol to the decoding tree of a real-valued FSD algorithm. The new Real-valued Fixed-Complexity Sphere Decoder (RFSD) algorithm derived achieves similar quasi-ML decoding performance as FSD, but with an average 70% reduction in computational complexity, as we demonstrate from both theoretical and implementation perspectives for Quadrature Amplitude Modulation (QAM)-MIMO systems.

Interval timing and trajectory in unequal amplitude movements

The Wing-Kristofferson (WK) model of movement timing emphasises the separation of central timer and motor processes. Several studies of repetitive timing have shown that increase in variability at longer intervals is attributable to timer processes; however, relatively little is known about the way motor aspects of timing are affected by task movement constraints. In the present study, we examined timing variability in finger tapping with differences in interval to assess central timer effects, and with differences in movement amplitude to assess motor implementation effects. Then, we investigated whether effects of motor timing observed at the point of response (flexion offset/tap) are also evident in extension, which would suggest that both phases are subject to timing control. Eleven participants performed bimanual simultaneous tapping, at two target intervals (400, 600 ms) with the index finger of each hand performing movements of equal (3 or 6 cm) or unequal amplitude (left hand 3, right hand 6 cm and vice versa). As expected, timer variability increased with the mean interval but showed only small, non-systematic effects with changes in movement amplitude. Motor implementation variability was greater in unequal amplitude conditions. The same pattern of motor variability was observed both at flexion and extension phases of movement. These results suggest that intervals are generated by a central timer, triggering a series of events at the motor output level including flexion and the following extension, which are explicitly represented in the timing system.