Slack-variable models versus Scheffé's mixture models

Slack-variable models are compared against Scheffé's polynomial model for mixture experiments. The notion of model equivalence and the use of various diagnostic measures provide effective tools in making such comparisons, particularly when the experimental region is highly constrained. It is demonstrated that the choice of the best fitting model, through variable selection, depends on which mixture component is selected as a slack variable, and on the size of the fitted model. In addition, the equivalence of two well-known representations of a complete mixture model is shown to be valid. Two numerical examples are presented.     

Bank Business Models at Zero Interest Rates

We propose a novel observation-driven finite mixture model for the study of banking data. The model accommodates time-varying component means and covariance matrices, normal and Student’s t distributed mixtures, and economic determinants of time-varying parameters. Monte Carlo experiments suggest that units of interest can be classified reliably into distinct components in a variety of settings. In an empirical study of 208 European banks between 2008Q1–2015Q4, we identify six business model components and discuss how their properties evolve over time. Changes in the yield curve predict changes in average business model characteristics.     

Sampling hyperparameters in hierarchical models: Improving on Gibbs for high-dimensional latent fields and large datasets

ABSTRACT

A common Bayesian hierarchical model is where high-dimensional observed data depend on high-dimensional latent variables that, in turn, depend on relatively few hyperparameters. When the full conditional distribution over latent variables has a known form, general MCMC sampling need only be performed on the low-dimensional marginal posterior distribution over hyperparameters. This improves on popular Gibbs sampling that computes over the full space. Sampling the marginal posterior over hyperparameters exhibits good scaling of compute cost with data size, particularly when that distribution depends on a low-dimensional sufficient statistic.     

A review of classic non-asymptotic methods for comparing two proportions by means of independent sampLES

The 2 × 2 tables used to present the data in an experiment for comparing two proportions by means of two observations of two independent binomial distributions may appear simple but are not. The debate about the best method to use is unending, and has divided statisticians into practically irreconcilable groups. In this article, all the available non-asymptotic tests are reviewed (except the Bayesian methodology). The author states which is the optimal (for each group), referring to the tables and programs that exist for them, and contrast the arguments used by supporters of each of the options. They also sort the tangle of solutions into "families", based on the methodology used and/or prior assumptions, and point out the most frequent methodological mistakes committed when comparing the different families.     

Do small cities affect bird assemblages? An evaluation from Patagonia

Urban Ecosystems - Most studies about the impact of urbanization on bird assemblages are from the Northern Hemisphere and most previous research has reported that cities reduced bird species...     

OECD: One or Many? Ranking Countries with a Composite Well-Being Indicator

In the social sciences it is hardly contested that “institutions matter”. Consequently the analysis of differences and similarities of institutions should be a routine task. Prevailing methods to the measurement of institutions are however problematic, in particular when they have to deal with different levels of measurement. To overcome this, in this paper we present an innovative method to the quantification of qualitative institutional data. We do this by, first, developing benchmarks for comparison based on Weberian ideal types. Then we identify and operationalise the dimensions and indicators to a nuanced measurement of institutions, after which we apply a careful and differentiated scoring, weighting and aggregation procedure in order to guarantee the highest standards of comparability, transparency and reliability of the method. Finally, we demonstrate our method by applying it to the analysis of institutional individualisation in European welfare institutions.     

Bibliometric analysis of production planning and control (1990–2016)

Production Planning and Control (PPC) has been one of the primary publishing outlets for operations management research for nearly three decades. This paper presents bibliometric analysis of the journal from its inception through 2016. PPC was analysed from six different perspectives to provide reliable and in-depth information about the journal’s performance and development. The analysis considered the development of the journal itself, the countries of contributing authors, authors’ academic and practitioner organisation affiliations, the top publishing and most cited authors, the most cited articles, and finally the topics of published papers through analysis of titles, keywords and abstracts. It was found that the journal is considered an outlet for both practice and academic research, reflecting changes over time in the landscape of operations management.