Convergence Rates for Probabilities of Moderate Deviations for Multidimensionally Indexed Random Variables

Let {X,Xn¯;n¯∈Z+d} be a sequence of i.i.d. real-valued random variables, and Sn¯=∑k¯≤n¯Xk¯, n¯∈Z+d. Convergence rates of moderate deviations are derived; that is, the rates of convergence to zero of certain tail probabilities of the partial sums are determined. For example, we obtain equivalent conditions for the convergence of the series ∑n¯b(n¯)ψ2(a(n¯))P{|Sn¯|≥a(n¯)ϕ(a(n¯))}, where a(n¯)=n11/α1⋯nd1/αd, b(n¯)=n1β1⋯ndβd, ϕ and ψ are taken from a broad class of functions. These results generalize and improve some results of Li et al. (1992) and some previous work of Gut (1980)

A Statistical Approach to the Alignment of fMRI Data

Multi-subject functional Magnetic Resonance Image studies are critical. The anatomical and functional structure varies across subjects, so the image alignment is necessary. We define a probabilistic model to describe functional alignment. Imposing a prior distribution, as the matrix Fisher Von Mises distribution, of the orthogonal transformation parameter, the anatomical information is embedded in the estimation of the parameters, i.e., penalizing the combination of spatially distant voxels. Real applications show an improvement in the classification and interpretability of the results compared to various functional alignment methods

A comparison of the CAR and DAGAR spatial random effects models with an application to diabetics rate estimation in Belgium

When hierarchically modelling an epidemiological phenomenon on a finite collection of sites in space, one must always take a latent spatial effect into account in order to capture the correlation structure that links the phenomenon to the territory. In this work, we compare two autoregressive spatial models that can be used for this purpose: the classical CAR model and the more recent DAGAR model. Differently from the former, the latter has a desirable property: its ρ parameter can be naturally interpreted as the average neighbor pair correlation and, in addition, this parameter can be directly estimated when the effect is modelled using a DAGAR rather than a CAR structure. As an application, we model the diabetics rate in Belgium in 2014 and show the adequacy of these models in predicting the response variable when no covariates are available

SIS 2017. Statistics and Data Science: new challenges, new generations

The 2017 SIS Conference aims to highlight the crucial role of the Statistics in Data Science. In this new domain of ‘meaning’ extracted from the data, the increasing amount of produced and available data in databases, nowadays, has brought new challenges. That involves different fields of statistics, machine learning, information and computer science, optimization, pattern recognition. These afford together a considerable contribute in the analysis of ‘Big data’, open data, relational and complex data, structured and no-structured. The interest is to collect the contributes which provide from the different domains of Statistics, in the high dimensional data quality validation, sampling extraction, dimensional reduction, pattern selection, data modelling, testing hypotheses and confirming conclusions drawn from the data

Pre-competition achievement goals within young sports performers

This thesis attempted to develop a clearer understanding of the pre-competition achievement goal perspectives that are held by young performers. The programme of research moves through three transitional stages incorporating three different methodologies. Specifically, the first two investigations which comprised Study 1 adopted a quantitative research methodology; Study 2 incorporated qualitative techniques; and the final investigation addressed the research question on an idiographic basis via a single subject design study. Firstly, an attempt is made to identify the major antecedents or precursors to states of goal involvement prior to a specific competitive situation. The first study examined the antecedents of pre-competition state goals within adolescent swimmers from an interactionist perspective. Results showed how levels of task and ego involvement prior to a specific race were related to both dispositional tendencies and situational factors within the race context. However, task orientation appeared to play a more powerful role than ego orientation in predicting their respective goal states. Furthermore, ego involvement was more strongly predicted by situational factors. The second investigation extended this question by investigating a sample of elite junior tennis players prior to a competitive match at the National Championships. In this way, the nature of the competitive context, with respect to goal or reward structure, changed from being more task-involving (individualistic-focused) to being more ego-involving (competitive-focused). Results showed how the players' goal states were related much more to perceptions of the context than to their reported goal orientation. Furthermore, task orientation did not emerge as a significant predictor of goal involvement. With these results in mind, the second stage of the thesis involved investigating, to a much greater depth, the motivational criteria which appeared to contribute to the development of goal orientation and the activation of goal involvement in the context of competition. For this purpose, qualitative interview techniques and an inductive content analysis were applied to a sample of seventeen elite junior tennis players. The findings suggested that the development of goal orientation and activation of pre-competition goal involvement rested on a complex interaction of internal and environmental factors. Specific general dimensions of influence included cognitive-developmental skills and experience, the motivational climate conveyed by significant others, the social and structural nature of tennis, and the match context. The information gathered from this study provided the impetus, rationale and theoretical foundation for the final study in this thesis. Employing a single subject multiple baseline across subjects design, the study investigated the effects of a structured environmental and task-based intervention programme which sought to influence precompetition goal involvement and related competitive cognitions within a small sample of adolescent national standard tennis players. Following a three month intervention period, the three targeted players reported pre-competition goal states which showed increased activation of the self-referent conception of achievement. Furthermore, each player fostered an attitude which valued the challenge of winning matches for internal reasons, as opposed to reasons associated with favourable social approval. These findings reinforced the practicability of educationlaction-based interventions designed to develop more adaptive motivational responses to competitive situations. The programme of research conducted in this thesis, therefore, highlights how precompetition achievement goal perspectives within young performers may be influenced, provided that one has a detailed understanding of the antecedents of this process. In so doing, this thesis alerts future research to the importance of working within an interactionist paradigm and with a measurement technology which can accurately assess goal states in a diverse number of sporting situations. In this way, our understanding of goal involvement, as an important achievement-related attentional state, may be greatly facilitated

General Course Catalog [2012/14]

Undergraduate Course Catalog, 2012/14https://repository.stcloudstate.edu/undergencat/1119/thumbnail.jp

General Course Catalog [January-June 2015]

Undergraduate Course Catalog, January-June 2015https://repository.stcloudstate.edu/undergencat/1121/thumbnail.jp