Higher-order Improvements of the Parametric Bootstrap for Long-memory Gaussian Processes

This paper determines coverage probability errors of both delta method and parametric bootstrap confidence intervals (CIs) for the covariance parameters of stationary long-memory Gaussian time series. CIs for the long-memory parameter d_0 are included. The results establish that the bootstrap provides higher-order improvements over the delta method. Analogous results are given for tests. The CIs and tests are based on one or other of two approximate maximum likelihood estimators. The first estimator solves the first-order conditions with respect to the covariance parameters of a "plug-in" log-likelihood function that has the unknown mean replaced by the sample mean. The second estimator does likewise for a plug-in Whittle log-likelihood. The magnitudes of the coverage probability errors for one-sided bootstrap CIs for covariance parameters for long-memory time series are shown to be essentially the same as they are with iid data. This occurs even though the mean of the time series cannot be estimated at the usual n^{1/2} rate.Asymptotics, confidence intervals, delta method, Edgeworth expansion, Gaussian process, long memory, maximum likelihood estimator, parametric bootstrap, t statistic, Whittle likelihood

Valid Edgeworth Expansions for the Whittle Maximum Likelihood Estimator for Stationary Long-memory Gaussian Time Series

In this paper, we prove the validity of an Edgeworth expansion to the distribution of the Whittle maximum likelihood estimator for stationary long-memory Gaussian models with unknown parameter theta in Theta subset R^{d_{theta}} . The error of the (s-2)-order expansion is shown to be o(n^{(s-2)/2}) -- the usual iid rate -- for a wide range of models, including the popular ARFIMA(p,d,q) models. The expansion is valid under mild assumptions on the behavior of spectral density and its derivatives in the neighborhood of the origin. As a by-product, we generalize a Theorem by Fox and Taqqu (1987) concerning the asymptotic behavior of Toeplitz matrices. Lieberman, Rousseau, and Zucker (2002) (LRZ) establish a valid Edgeworth expansion for the maximum likelihood estimator for stationary long-memory Gaussian models. For a significant class of models, their expansion is shown to have an error of o(n-1). The results given here improve upon those of LRZ in that the results provide an Edgeworth expansion for an asymptotically efficient estimator, as LRZ do, but the error of the expansion is shown to be o(n^{-(s-2)/2}), not o(n^{-1}), for a broad range of models.ARFIMA, Edgeworth expansion, Long Memory, Whittle estimator

Higher-order Improvements of the Parametric Bootstrap for Long-memory Gaussian Processes

This paper determines coverage probability errors of both delta method and parametric bootstrap confidence intervals (CIs) for the covariance parameters of stationary long-memory Gaussian time series. CIs for the long-memory parameter d 0 are included. The results establish that the bootstrap provides higher-order improvements over the delta method. Analogous results are given for tests. The CIs and tests are based on one or other of two approximate maximum likelihood estimators. The first estimator solves the first-order conditions with respect to the covariance parameters of a “plug-in” log-likelihood function that has the unknown mean replaced by the sample mean. The second estimator does likewise for a plug-in Whittle log-likelihood. The magnitudes of the coverage probability errors for one-sided bootstrap CIs for covariance parameters for long-memory time series are shown to be essentially the same as they are with iid data. This occurs even though the mean of the time series cannot be estimated at the usual n 1 /2 rate

The characteristics of cognitive neuroscience tests in a schizophrenia cognition clinical trial: Psychometric properties and correlations with standard measures.

In comparison to batteries of standard neuropsychological tests, cognitive neuroscience tests may offer a more specific assessment of discrete neurobiological processes that may be aberrant in schizophrenia. However, more information regarding psychometric properties and correlations with standard neuropsychological tests and functional measures is warranted to establish their validity as treatment outcome measures. The N-back and AX-Continuous Performance Task (AX-CPT) are two promising cognitive neuroscience tests designed to measure specific components of working memory and contextual processing respectively. In the current study, we report the psychometric properties of multiple outcome measures from these two tests as well as their correlations with standard neuropsychological measures and functional capacity measures. The results suggest that while the AX-CPT and N-back display favorable psychometric properties, they do not exhibit greater sensitivity or specificity with functional measures than standard neurocognitive tests

Valid Edgeworth Expansions for the Whittle Maximum Likelihood Estimator for Stationary Long-memory Gaussian Time Series

In this paper, we prove the validity of an Edgeworth expansion to the distribution of the Whittle maximum likelihood estimator for stationary long-memory Gaussian models with unknown parameter donpap26_black.jpg (3566 bytes) . The error of the (s-2)-order expansion is shown to be o ( n ( s -2)/2 ) – the usual iid rate — for a wide range of models, including the popular ARFIMA(p,d,q) models. The expansion is valid under mild assumptions on the behavior of spectral density and its derivatives in the neighborhood of the origin. As a by-product, we generalize a Theorem by Fox and Taqqu (1987) concerning the asymptotic behavior of Toeplitz matrices. Lieberman, Rousseau, and Zucker (2002) (LRZ) establish a valid Edgeworth expansion for the maximum likelihood estimator for stationary long-memory Gaussian models. For a significant class of models, their expansion is shown to have an error of o ( n -1 ). The results given here improve upon those of LRZ in that the results provide an Edgeworth expansion for an asymptotically efficient estimator, as LRZ do, but the error of the expansion is shown to be o ( n -( s -2)/2 ), not o ( n -1 ), for a broad range of models

See no Evil: Challenges of security surveillance and monitoring

While the development of intelligent technologies in security surveillance can augment human capabilities, they do not replace the role of the operator entirely; as such, when developing surveillance support it is critical that limitations to the cognitive system are taken into account. The current article reviews the cognitive challenges associated with the task of a CCTV operator: visual search and cognitive/perceptual overload, attentional failures, vulnerability to distraction, and decision-making in a dynamically evolving environment. While not directly applied to surveillance issues, we suggest that the NSEEV (noticing – salience, effort, expectancy, value) model of attention could provide a useful theoretical basis for understanding the challenges faced in detection and monitoring tasks. Having identified cognitive limitations of the human operator, this review sets out a research agenda for further understanding the cognitive functioning related to surveillance, and highlights the need to consider the human element at the design stage when developing technological solutions to security surveillance

The evolution of language: a comparative review

For many years the evolution of language has been seen as a disreputable topic, mired in fanciful "just so stories" about language origins. However, in the last decade a new synthesis of modern linguistics, cognitive neuroscience and neo-Darwinian evolutionary theory has begun to make important contributions to our understanding of the biology and evolution of language. I review some of this recent progress, focusing on the value of the comparative method, which uses data from animal species to draw inferences about language evolution. Discussing speech first, I show how data concerning a wide variety of species, from monkeys to birds, can increase our understanding of the anatomical and neural mechanisms underlying human spoken language, and how bird and whale song provide insights into the ultimate evolutionary function of language. I discuss the ‘‘descended larynx’ ’ of humans, a peculiar adaptation for speech that has received much attention in the past, which despite earlier claims is not uniquely human. Then I will turn to the neural mechanisms underlying spoken language, pointing out the difficulties animals apparently experience in perceiving hierarchical structure in sounds, and stressing the importance of vocal imitation in the evolution of a spoken language. Turning to ultimate function, I suggest that communication among kin (especially between parents and offspring) played a crucial but neglected role in driving language evolution. Finally, I briefly discuss phylogeny, discussing hypotheses that offer plausible routes to human language from a non-linguistic chimp-like ancestor. I conclude that comparative data from living animals will be key to developing a richer, more interdisciplinary understanding of our most distinctively human trait: language

Coccidioidomycosis as a Common Cause of Community-acquired Pneumonia

The early manifestations of coccidioidomycosis (valley fever) are similar to those of other causes of community-acquired pneumonia (CAP). Without specific etiologic testing, the true frequency of valley fever may be underestimated by public health statistics. Therefore, we conducted a prospective observational study of adults with recent onset of a lower respiratory tract syndrome. Valley fever was serologically confirmed in 16 (29%) of 55 persons (95% confidence interval 16%–44%). Antimicrobial medications were used in 81% of persons with valley fever. Symptomatic differences at the time of enrollment had insufficient predictive value for valley fever to guide clinicians without specific laboratory tests. Thus, valley fever is a common cause of CAP after exposure in a disease-endemic region. If CAP develops in persons who travel or reside in Coccidioides-endemic regions, diagnostic evaluation should routinely include laboratory evaluation for this organism