Manuel G. Scotto

Modelling uncertainty in long-term predictions of significant wave height

Abstract This paper deals with the application of different methods to estimate the occurrences of high sea states. A case study of the Norwegian continental shelf is considered. The Annual Maxima Method and the Peak Over Threshold Method are used to obtain return values for 25, 50 and 100 years. Several parametric models are used to fit the long-term distribution of significant wave height and to obtain predictions of extremes values. It is shown that the prediction of these sea states depends very much on the tail behaviour of the fitted distribution.

Quantitating progression in ALS

The authors prospectively studied the value of clinical and neurophysiologic measurements in assessing progression in ALS. Motor unit number estimation (MUNE) and the neurophysiologic index (NI) were significantly correlated with ADM strength (maximal voluntary isometric contraction force in the abductor digiti minimi muscle [MVIC-ADM]). MUNE and the NI were reliable, but the NI showed a lower variation. On assessing progression at 3, 6, and 12 months, MUNE, NI, and MVIC-ADM showed the highest rate of change. The NI is a potentially useful new neurophysiologic measurement.

Clinical and neurophysiological evaluation of progression in amyotrophic lateral sclerosis

There is a need for a sensitive neurophysiological measure of disease progression in following the course of patients with amyotrophic lateral sclerosis (ALS). We studied two groups of nine ALS patients, one with slow progression (Group A) and the other with rapid progression (Group B). We evaluated muscle strength scores using the Medical Research Council (MRC) scale in limb and trunk muscles, forced vital capacity (FVC), and ALS functional rating scale (ALS‐FRS) scores. Maximal voluntary isometric contraction (MVIC) of the abductor digiti minimi muscle (ADM) was measured, using a digital device. We also measured M‐wave amplitude and area in the ADM, and the distal motor latency and F‐wave frequency in the ulnar nerve; from these data, the neurophysiological index (NI) was calculated, as described previously. In both groups, the NI was the most sensitive measure of change, with the smallest coefficient of variation. We conclude that the NI, which requires no special technology and no new clinical or technical skills to use, is sensitive to change, and therefore may be useful in clinical trials, as well as in a clinical setting. Muscle Nerve 28: 630–633, 2003

Modelling the long-term time series of significant wave height with non-linear threshold models

Linear autoregressive models and non-linear threshold autoregressive (TAR) models are used in the present work to describe the time series of the significant wave height of sea-states at Figueira da Foz, located in the Portuguese coast. The seasonal components of this series are identified and a TAR model with two regimes is proposed. A simulation study was carried out with the purpose of verifying if both the non-linear and linear models are suited to describe the probabilistic structure of the process. It is shown that both methods are adequate to describe the lower statistical moments of the original data, but the non-linear model represents better the skewness and the kurtosis of the data.

Neurophysiological markers in familial amyloid polyneuropathy patients: Early changes

OBJECTIVE Familial amyloid polyneuropathy-type I (FAP-I) is a hereditary, axonal, sensory-motor and autonomic polyneuropathy, with early involvement of small fibres. Liver transplantation is the only effective therapy in FAP, but should be performed early in the course of the disease. Reliable quantitative methods that could allow the determination of early changes in the peripheral nerve function are essential. Our aim was to find sensitive neurophysiological markers in FAP-I. METHODS Eighty-one FAP-I patients were included in this study. They were divided into two groups (G1, asymptomatic FAP-I mutation carriers; G2, early symptomatic). Seventy-six healthy controls formed a control group (G3). Nerve conduction studies, needle electromyography with motor unit potential analysis of the extensor digitorum brevis, RR interval and sympathetic skin response (SSR) were analyzed. RESULTS The amplitudes of the motor response of the peroneus nerve and of the plantar SSR were significantly lower in G1 compared to G3. No other differences were found between those two groups. With a cut-off point of 0.2mV for plantar SSR, its sensitivity and specificity are 0.53 and 0.95, respectively. The positive predictive value and the negative predictive value are 0.82. CONCLUSIONS SSR response at foot is a useful measurement to detect early dysfunction of peripheral nerve fibres in FAP-I. Its abnormality should be considered a warning sign and lead to a careful clinical assessment. SIGNIFICANCE SSR is a useful neurophysiological marker in FAP-I.

Reproducibility of neurophysiological and myometric measurement in the ulnar nerve-abductor digiti minimi system.

Reliability in strength and neurophysiological measurements is important in evaluating progression of neuromuscular diseases. No data are available on the variability of neurophysiological parameters as compared with maximal voluntary isometric contraction (MVIC) in the same muscles, in healthy subjects. A control population of 26 healthy subjects was studied twice on different days. We evaluated the reliability of neurophysiological parameters obtained from bilateral ulnar nerve stimulation, recording the response over the abductor digiti minimi (ADM) muscle, including distal motor latency, compound muscle potential amplitude and area, F‐wave frequency and mean F‐wave latency, and the derived neurophysiological index that we have described previously. MVIC force was measured in each session in both ADM muscles. The variances between the grouped data obtained in the two recording sessions were identical, indicating a low intrinsic variability with this experimental methodology. Comparison of the mean values obtained in the two sessions revealed no statistically significant differences. The reliability of these neurophysiological and strength measurements in the same nerve/muscle system suggests they may be useful in comparing the dynamics of weakness and neurophysiological change in neuromuscular disease.

Thinning-based models in the analysis of integer-valued time series: a review:

This article aims at providing a comprehensive survey of recent developments in the field of integer-valued time series modelling, paying particular attention to models obtained as discrete counterparts of conventional autoregressive moving average and bilinear models, and based on the concept of thinning. Such models have proven to be useful in the analysis of many real-world applications ranging from economy and finance to medicine. We review the literature of the most relevant thinning operators proposed in the analysis of univariate and multivariate integer-valued time series with either finite or infinite support. Finally, we also outline and discuss possible directions of future research.

Extremes of Some Sub-Sampled Time Series

_This paper attempts to find the possibilities of simplifying a multiple time series. We consider a dynamic factor model, Z_t=[sum]_i=1-super-m Lambda inf>iX_t-i+G epsilon _t, where Z_t is a k-dimensional Gaussian stationary time series, X_t is an unobservable r-dimensional factor series (K>=r) and epsilon _t is a (K - r) -dimensional white noise series, fully independent of {X_t}. The model is for reducing the dimension of time effect of the series, because the error term is independent of time. This article starts with an example showing that two independent AR(1) series can be generated by one series under this model. Mathematical properties of the model are studied. Its relations with other time series models are also discussed. Copyright 2003 Blackwell Publishing Ltd.Let X_k be a stationary time series and y_k=X_kM be the sub-sampled series corresponding to a fixed systematic sampling interval M > 1. In this paper, we use a point process approach to study the effect of the sub sampling on the extremal properties of Y_k when X_k is a linear process with heavy-tailed innovations. We prove complete point process convergence theorems which enable us to give in detail the weak limiting behaviour of maxima of the sub-sampled process and to compare it with that of the original process. The results both exemplify the findings of a study by Robinson and Tawn (2000) and offer more precise details for the class of linear models. Motivation comes from the comparison of schemes for monitoring financial and environmental processes. Copyright 2003 Blackwell Publishing Ltd.

Clinical patterns in progressive muscular atrophy (PMA): A prospective study

Progressive muscular atrophy (PMA) is a form of motor neuron disease, but its outcome is not well defined, and the aim was to study the pattern of clinical progression in PMA. We studied 10 patients prospectively for 12 months. None showed clinical signs of upper motor neuron involvement at presentation or during follow‐up, and all had normal transcranial magnetic stimulation studies. Four had upper limb onset, four lower limb onset and two axial onset. We used neurophysiological and strength measurements and a clinical rating scale (ALS‐FRS). Seven other patients presenting with a PMA syndrome developed upper motor neuron signs during a one‐year period of observation and were excluded from the study. The rate of progression was variable. At six months, only motor unit number estimation (MUNE) and ALS‐FRS had decreased significantly. The Neurophysiological Index (NI) and M‐wave amplitude measurements decreased at 12 months. Two patients with axial‐onset disease progressed rapidly to respiratory failure. Overall the pattern of change resembled that of ALS, although some patients progressed very slowly. Axial onset, however, predicts the early onset of respiratory failure, and a poor prognosis.

Bivariate binomial autoregressive models

This paper introduces new classes of bivariate time series models being useful to fit count data time series with a finite range of counts. Motivation comes mainly from the comparison of schemes for monitoring tourism demand, stock data, production and environmental processes. All models are based on the bivariate binomial distribution of Type II. First, a new family of bivariate integer-valued GARCH models is proposed. Then, a new bivariate thinning operation is introduced and explained in detail. The new thinning operation has a number of advantages including the fact that marginally it behaves as the usual binomial thinning operation and also that allows for both positive and negative cross-correlations. Based upon this new thinning operation, a bivariate extension of the binomial autoregressive model of order one is introduced. Basic probabilistic and statistical properties of the model are discussed. Parameter estimation and forecasting are also covered. The performance of these models is illustrated through an empirical application to a set of rainy days time series collected from 2000 up to 2010 in the German cities of Bremen and Cuxhaven.