Recent advances in directional statistics

Mainstream statistical methodology is generally applicable to data observed in Euclidean space. There are, however, numerous contexts of considerable scientific interest in which the natural supports for the data under consideration are Riemannian manifolds like the unit circle, torus, sphere and their extensions. Typically, such data can be represented using one or more directions, and directional statistics is the branch of statistics that deals with their analysis. In this paper we provide a review of the many recent developments in the field since the publication of Mardia and Jupp (1999), still the most comprehensive text on directional statistics. Many of those developments have been stimulated by interesting applications in fields as diverse as astronomy, medicine, genetics, neurology, aeronautics, acoustics, image analysis, text mining, environmetrics, and machine learning. We begin by considering developments for the exploratory analysis of directional data before progressing to distributional models, general approaches to inference, hypothesis testing, regression, nonparametric curve estimation, methods for dimension reduction, classification and clustering, and the modelling of time series, spatial and spatio-temporal data. An overview of currently available software for analysing directional data is also provided, and potential future developments discussed.Comment: 61 page

Evolution of statistical analysis in empirical software engineering research: Current state and steps forward

Software engineering research is evolving and papers are increasingly based on empirical data from a multitude of sources, using statistical tests to determine if and to what degree empirical evidence supports their hypotheses. To investigate the practices and trends of statistical analysis in empirical software engineering (ESE), this paper presents a review of a large pool of papers from top-ranked software engineering journals. First, we manually reviewed 161 papers and in the second phase of our method, we conducted a more extensive semi-automatic classification of papers spanning the years 2001--2015 and 5,196 papers. Results from both review steps was used to: i) identify and analyze the predominant practices in ESE (e.g., using t-test or ANOVA), as well as relevant trends in usage of specific statistical methods (e.g., nonparametric tests and effect size measures) and, ii) develop a conceptual model for a statistical analysis workflow with suggestions on how to apply different statistical methods as well as guidelines to avoid pitfalls. Lastly, we confirm existing claims that current ESE practices lack a standard to report practical significance of results. We illustrate how practical significance can be discussed in terms of both the statistical analysis and in the practitioner's context.Comment: journal submission, 34 pages, 8 figure

An Empirical Glimpse on MSEs Four MENA Countries

The Economic Research Forum (ERF) produced a one-off survey of micro & small private enterprises (MSE) in a number of Middle East and North African countries (MENA). It contains sufficient information to fit a production function and additional information about the owner’s education type; the scope of the market; and the type of technology. Further, it provides information about perceived constraints to production. We test the effect of these factors on technical progress. We believe that empirical research of policy issues can help promote the making of ‘evidence-based policies’ in the MENA countries.Micro-small Private Enterprise; Production Function; Stochastic Dominance.

An Empirical Glimpse on MSEs Four MENA Countries

The Economic Research Forum (ERF) produced a one-off survey of micro & small private enterprises (MSE) in a number of Middle East and North African countries (MENA). It contains sufficient information to fit a production function and additional information about the owner’s education type; the scope of the market; and the type of technology. Further, it provides information about perceived constraints to production. We test the effect of these factors on technical progress. We believe that empirical research of policy issues can help promote the making of ‘evidence-based policies’ in the MENA countries.Micro-small private enterprise; production function; stochastic dominance.