The R package kerdiest has been designed for computing kernel estimators of the distribution function and other related functions. Because of its usefulness in real applications, the bandwidth parameter selection problem has been considered, and a cross-validation method and two of plug-in type have been implemented. Moreover, three relevant functions in nature hazards have also been programmed. The package is completed with two interesting data sets, one of geological type (a complete catalogue of the earthquakes occurring in the northwest of the Iberian Peninsula) and another containing the maximum peak flow levels of a river in the United States of America.

Comparison of emotion perception in music and prosody has the potential to contribute to an understanding of their speculated shared evolutionary origin. Previous research suggests shared sensitivity to and processing of music and speech, but less is known about how emotion perception in the auditory domain might be influenced by individual differences. Personality, emotional intelligence, gender, musical training and age exert some influence on discrete, summative judgments of perceived emotion in music and speech stimuli. However, music and speech are temporal phenomena, and little is known about whether individual differences influence moment-by-moment perception of emotion in these domains. A behavioral study collected two main types of data: continuous ratings of perceived emotion while listening to extracts of music and speech, using a computer interface which modeled emotion on two dimensions (arousal and valence), and demographic information including measures of personality (TIPI) and emotional intelligence (TEIQue-SF). Functional analysis of variance on the time series data revealed a small number of statistically significant differences associated with Emotional Stability, Agreeableness, musical training and age. The results indicate that individual differences exert limited influence on continuous judgments of dynamic, naturalistic expressions. We suggest that this reflects a reliance on acoustic cues to emotion in moment-by-moment judgments of perceived emotions and is further evidence of the shared sensitivity to and processing of music and speech.

SUMMARYPrediction of maximum ozone concentration is of great importance, especially to alert the population and to allow the authorities to take preventive measures soon enough. Ozone concentration and meteoro-logical variables are now observed each hour or every 10 min so that we nearly get continuous observations along time, i.e. functions, as covariates. Much work has been done in the statistical community to propose effective models for predicting ozone concentration one day ahead, but there has been much less effort to study methods that take the functional nature of these data into account. We propose here two non-linear models based on kernel estimators that handle the functional characteristics of the data by means of a measure of proximity between observed functions. In addition, we use additive ideas to take exogeneous variables into account without being too sensitive to dimensionality effects.Such procedures are called multivariate functional non-parametric approaches, since our models/estimates are non-parametric (because of the non-linear structure linking the explanatory and the response variables), functional (because the variables are curves) and multi-dimensional (because we can have many functional explanatory variables).These models are used to forecast maximum ozone concentration in Toulouse (France). We compare them to more classical techniques and the results are promising.

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