Test-retest reliability of the magnetic mismatch negativity response to sound duration and omission deviants

Mismatch negativity (MMN) is a neurophysiological measure of auditory novelty detection that could serve as a translational biomarker of psychiatric disorders, such as schizophrenia. However, the replicability of its magnetoencephalographic (MEG) counterpart (MMNm) has been insufficiently addressed. In the current study, test-retest reliability of the MMNm response to both duration and omission deviants was evaluated over two MEG sessions in 16 healthy adults. MMNm amplitudes and latencies were obtained at both sensor- and source-level using a cortically-constrained minimum-norm approach. Intraclass correlations (ICC) were derived to assess stability of MEG responses over time. In addition, signal-to-noise ratios (SNR) and within-subject statistics were obtained in order to determine MMNm detectability in individual participants. ICC revealed robust values at both sensor- and source-level for both duration and omission MMNm amplitudes (ICC = 0.81-0.90), in particular in the right hemisphere, while moderate to strong values were obtained for duration MMNm and omission MMNm peak latencies (ICC = 0.74-0.88). Duration MMNm was robustly identified in individual participants with high SNR, whereas omission MMNm responses were only observed in half of the participants. Our data indicate that MMNm to unexpected duration changes and omitted sounds are highly reproducible, providing support for the use of MEG-parameters in basic and clinical research

Testing Isotropic Universe Using the Gamma-Ray Burst Data of Fermi / GBM

The sky distribution of Gamma-Ray Bursts (GRBs) has been intensively studied by various groups for more than two decades. Most of these studies test the isotropy of GRBs based on their sky number density distribution. In this work we propose an approach to test the isotropy of the Universe through inspecting the isotropy of the properties of GRBs such as their duration, fluences and peak fluxes at various energy bands and different time scales. We apply this method on the {\em Fermi} / Gamma-ray Burst Monitor (GBM) data sample containing 1591 GRBs. The most noticeable feature we found is near the Galactic coordinates $l\approx 30^\circ$, $b\approx 15^\circ$ and radius $r\approx 20^\circ-40^\circ$. The inferred probability for the occurrence of such an anisotropic signal (in a random isotropic sample) is derived to be less than a percent in some of the tests while the other tests give results consistent with isotropy. These are based on the comparison of the results from the real data with the randomly shuffled data samples. Considering large number of statistics we used in this work (which some of them are correlated to each other) we can anticipate that the detected feature could be result of statistical fluctuations. Moreover, we noticed a considerably low number of GRBs in this particular patch which might be due to some instrumentation or observational effects that can consequently affect our statistics through some systematics. Further investigation is highly desirable in order clarify about this result, e.g. utilizing a larger future {\em Fermi} / GBM data sample as well as data samples of other GRB missions and also looking for possible systematics.Comment: 17 pages, 10 figures, 4 tables, accepted for publication in The Astrophysical Journa

Testing Isotropic Universe Using the Gamma-Ray Burst Data of Fermi / GBM

The sky distribution of Gamma-Ray Bursts (GRBs) has been intensively studied by various groups for more than two decades. Most of these studies test the isotropy of GRBs based on their sky number density distribution. In this work we propose an approach to test the isotropy of the Universe through inspecting the isotropy of the properties of GRBs such as their duration, fluences and peak fluxes at various energy bands and different time scales. We apply this method on the {\em Fermi} / Gamma-ray Burst Monitor (GBM) data sample containing 1591 GRBs. The most noticeable feature we found is near the Galactic coordinates $l\approx 30^\circ$, $b\approx 15^\circ$ and radius $r\approx 20^\circ-40^\circ$. The inferred probability for the occurrence of such an anisotropic signal (in a random isotropic sample) is derived to be less than a percent in some of the tests while the other tests give results consistent with isotropy. These are based on the comparison of the results from the real data with the randomly shuffled data samples. Considering large number of statistics we used in this work (which some of them are correlated to each other) we can anticipate that the detected feature could be result of statistical fluctuations. Moreover, we noticed a considerably low number of GRBs in this particular patch which might be due to some instrumentation or observational effects that can consequently affect our statistics through some systematics. Further investigation is highly desirable in order clarify about this result, e.g. utilizing a larger future {\em Fermi} / GBM data sample as well as data samples of other GRB missions and also looking for possible systematics.Comment: 17 pages, 10 figures, 4 tables, accepted for publication in The Astrophysical Journa

Modelling of Sunshine Duration for Peninsular Malaysia

Knowledge of solar radiation at any area is important for designing solar energy conversion systems, and is also useful for ecophysiological studies. In the present study, we have analysed the daily sunshine duration records for Peninsular Malaysia and apply them in solar radiation modelling. Firstly, we fitted Angstrom type equation to solar radiation and sunshine duration, to deter mine the relation between them. We have found that the seasonal variations of the regression parameters, are different for even two nearby locations. Variation of solar radiation within a small area are also noticable. Secondly, we have studied on the probability distribution nature of daily relative sunshine duration. Daily relative sunshine duration data are fitted to three models. Parameters of the models are estimated only from the monthly mean. Kolmogorov-Smirnov test is applied to determine the goodness of fit. We have found that the four stations can model led by two distributions. Data are also fitted to well known beta distribution model. The effect of variance is also presented. Finally, time series analysis of daily relative sunshine duration data are presented in chapter 4. Using gaussian mapping technique, nonstationary and non-normal distribution nature of the sunshine can be transformed into stationary and normal distribution. The autocorrelation function and partial autocorrelation function show the characteristics of autoregressive process. Results from the Box-Pierce and Ljung-Box statistics indicate that the first order autoregressive model is not suitable, while the second order autoregressive model gives satisfactory results. The relative sunshine duration of any day is dependent on the previous two days

Model risk in backtesting risk measures

Under the Basel II regulatory framework non-negligible statistical problems arise when backtesting risk measures. In this setting backtests often become infeasible due to a low number of violations leading to heavy size distortions. According to Escanciano and Olmo (2010, 2011) these problems persist when incorporating estimation and model risk by adjusting the asymptotic variance of the test statistics. In this paper, we analyze backtests based on hit and duration sequences in a univariate framework by running a simulation study in order to identify the problems of backtests that examine the adequacy of Value at Risk measures. One main finding indicates that backtests of all classes show heavy size distortions. These problems for the relevant Basel II set-up, however, cannot be alleviated by modifying backtests in a way that accounts for estimation risk or misspecification risk

Comparison of MSACD models

We propose a new framework for modelling time dependence in duration processes on financial markets. The well known autoregressive conditional duration (ACD) approach introduced by Engle and Russell (1998) will be extended in a way that allows the conditional expectation of the duration process to depend on an unobservable stochastic process which is modelled via a Markov chain. The Markov switching ACD model (MSACD) is a very flexible tool for description and forecasting of financial duration processes. In addition, the introduction of an unobservable, discrete valued regime variable can be justified in the light of recent market microstructure theories. In an empirical application we show that the MSACD approach is able to capture several specific characteristics of inter trade durations while alternative ACD models fail. JEL classification: C22, C25, C41, G1

Inpainting of long audio segments with similarity graphs

We present a novel method for the compensation of long duration data loss in audio signals, in particular music. The concealment of such signal defects is based on a graph that encodes signal structure in terms of time-persistent spectral similarity. A suitable candidate segment for the substitution of the lost content is proposed by an intuitive optimization scheme and smoothly inserted into the gap, i.e. the lost or distorted signal region. Extensive listening tests show that the proposed algorithm provides highly promising results when applied to a variety of real-world music signals

A Simple Test for the Absence of Covariate Dependence in Hazard Regression Models

This paper extends commonly used tests for equality of hazard rates in a two-sample or k-sample setup to a situation where the covariate under study is continuous. In other words, we test the hypothesis that the conditional hazard rate is the same for all covariate values, against the omnibus alternative as well as more specific alternatives, when the covariate is continuous. The tests developed are particularly useful for detecting trend in the underlying conditional hazard rates or changepoint trend alternatives. Asymptotic distribution of the test statistics are established and small sample properties of the tests are studied. An application to the e¤ect of aggregate Q on corporate failure in the UK shows evidence of trend in the covariate e¤ect, whereas a Cox regression model failed to detect evidence of any covariate effect. Finally, we discuss an important extension to testing for proportionality of hazards in the presence of individual level frailty with arbitrary distribution