Predicting burrowing owl flight trajectories in urban environments

Urban Ecosystems - It is important to understand how animals respond to changes in landscape structure, especially when considering habitat alteration and urbanization. Using the burrowing owl...     

A General Approach To Nonparametric Histogram Estimation

We note that some classical functional estimation problems may be reduced to a general unique framework and study an estimator within this general framework that reduces to the classical histogram type estimators in various examples presented. The convergence in probability and the almost complete convergence of this general estimator are studied obtaining convergence conditions which reduce to the classical conditions in each case. Finally, this general framework provides conditions for the convergence of the finite dimensional distributions of the associated empirical process.     

Testing parametric models in linear‐directional regression

This paper presents a goodness‐of‐fit test for parametric regression models with scalar response and directional predictor, that is, a vector on a sphere of arbitrary dimension. The testing procedure is based on the weighted squared distance between a smooth and a parametric regression estimator, where the smooth regression estimator is obtained by a projected local approach. Asymptotic behaviour of the test statistic under the null hypothesis and local alternatives is provided, jointly with a consistent bootstrap algorithm for application in practice. A simulation study illustrates the performance of the test in finite samples. The procedure is applied to test a linear model in text mining.     

Ordinal models and generalized estimating equations to evaluate disease severity

Many assays have been carried out in Capsicum spp. in order to evaluate its resistance to Phytophthora capsici , which causes blight and considerable yield loss. An assay aiming at the selection of resistant pepper and bell pepper genotypes to P. capsici was jointly performed in the laboratory of the Phytopathological Clinic of Entomology, Phytopathology and Agricultural Zoology and in the experimental area of the Plant Production Department, both located at ESALQ, University of São Paulo, Brazil. The data set for this assay comes from ordinal categorized random variables, whose analysis does not generally take into account the ordinal nature of the responses, but instead, builds indexes, among other measures, in order to evaluate the resistance of the studied genotypes. This work presents ordinal generalized linear fits in order to evaluate blight severity as well as to identify and select new resources to the pathogen. It also analyses the estimating equations proposed by Liang & Zeger (1986a, b) in order to obtain an infection pattern for the disease. From the fit of the cumulative logit models, valuable genotypes are identified for genetic breeding programs.     

Comments on “Sums,Products, and Ratios of Non-Central Beta Variables” by Saralees Nadarajah

Brief comments on “Sums, Products, and Ratios of Non-Central Beta Variables” by Saralees Nadarajah, which appeared in Communications in Statistics – Theory and Methods, Volume 34, Issue 1, pp. 89–100.     

Some comments on escoufier's RV- coefficient as a sensitivity measure in principal component analysis

The RV-coefficient (Escoufier, 1973; Robert and Escoufier, 1976) is studied as a sensitivity coefficient of the subspace spanned by dominant eigenvectors in principal component analysis. We use the perturbation expansion up to second order term of the corresponding projection matrix. The relationship with the measures by Benasseni (1990) and Krzanowski (1979) is also discussed.     

Physically active undergraduates: Motivational and emotional profiles

Abstract

Objectives: The aim was to determine the motivational profiles – including variables from the theory of self-determination and emotional intelligence – of active undergraduates, and to examine their relationship with physical activity. Participants: Six hundred and fifteen undergraduates participated in the study. Methods: Trait Meta-Mood Scale, Basic Psychological Needs in Exercise Scale, Behavioral Regulation in Exercise Questionnaire and Habitual Physical Activity Questionnaire were administered. Cluster analysis was used to identify the motivational profiles. Results: Two motivational profiles were found. One of the motivational profiles included the participants with high levels of satisfaction of the basic psychological needs and self-determined motivation; moderately high levels of emotional clarity and repair; and low levels of non-self-determined motivation. Further, this group showed the highest rates of physical practice than its counterpart. Conclusions: The combination of self-determination theory and emotional intelligence should be considered when examining adherence to physical activity.