The Basket-peg, Dollar-peg and Floating: A Comparative Analysis of Exchange Rate Regimes

currency basket, financial crisis, exchange rate regime, dollar-peg, basket-peg, floating exchange rates, optimal weights

Statistical modelling with additive Gaussian process priors

Regression with Gaussian process (GP) priors has become increasingly popular due to its ability to model complex relationships between variables and handle auto-correlation in the data through the covariance function of the process, called kernel. Despite its popularity, the statistical modelling aspect of GP regression has received relatively limited attention. In this thesis, we explore a regression model where the regression function can be decomposed into a sum of lower-dimensional functions, akin to the principles of Generalised Additive Models (Hastie and Tibshirani, 1990). We propose additive interaction modelling using a class of hierarchical ANOVA decomposition kernel. This flexible statistical modelling framework naturally accommodates interaction effects of any order without increasing the number of model parameters. Our approach facilitates straightforward assessment and comparison of models with different interaction structures through the model marginal likelihood. We also demonstrate how this framework enhances the interpretability of complex data structures, especially when combined with the concept of kernel centring. The second segment of the thesis focuses on the computational aspects of implementing the proposed additive models for handling large-scale data structured in multidimensional grids. Such structured data often arise in scenarios involving multilevel repeated measurements, as commonly seen in spatio-temporal analysis or medical, behavioural, and psychological studies. Leveraging the Kronecker product structure within the covariance matrix, we reduce the time complexity to O(n3) and storage requirements to O(n2). We extend existing work in the GP literature to encompass all models under hierarchical ANOVA decomposition kernels. Additionally, we address issues related to incomplete grids and various missingness mechanisms. We illustrate the practical application of our proposed methodologies using both simulated and real-world spatio-temporal and longitudinal data

Hyperreactivity to weak acoustic stimuli and prolonged acoustic startle latency in children with autism spectrum disorders

BACKGROUND: People with autism spectrum disorders (ASD) are known to have enhanced auditory perception, however, acoustic startle response to weak stimuli has not been well documented in this population. The objectives of this study are to evaluate the basic profile of acoustic startle response, including peak startle latency and startle magnitude to weaker stimuli, in children with ASD and typical development (TD), and to evaluate their relationship to ASD characteristics. METHODS: We investigated acoustic startle response with weak and strong acoustic stimuli in 12 children with ASD and 28 children with TD, analyzing the relationship between startle measures and quantitative autistic traits assessed with the Social Responsiveness Scale (SRS). The electromyographic activity of the left orbicularis oculi muscle to acoustic stimuli of 65 to 115 dB sound pressure level (SPL), in increments of 5 dB, was measured to evaluate acoustic startle response. The average eyeblink magnitude for each acoustic stimuli intensity and the average peak startle latency of acoustic startle response were evaluated. RESULTS: The magnitude of the acoustic startle response to weak stimuli (85 dB or smaller) was greater in children with ASD. The peak startle latency was also prolonged in individuals with ASD. The average magnitude of the acoustic startle response for stimulus intensities greater than 85 dB was not significantly larger in the ASD group compared with the controls. Both greater startle magnitude in response to weak stimuli (particularly at 85 dB) and prolonged peak startle latency were significantly associated with total scores, as well as several subscales of the SRS in the whole sample. We also found a significant relationship between scores on the social cognition subscale of the SRS and the average magnitude of the acoustic startle response for stimulus intensities of 80 and 85 dB in the TD group. CONCLUSIONS: Children with ASD exhibited larger startle magnitude to weak stimuli and prolonged peak startle latency. These startle indices were related to several characteristics of ASD. A comprehensive investigation of acoustic startle response, including the magnitude of startle responses to weak stimuli and peak startle latency, might further our understanding of the neurophysiological impairments underlying ASD

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