Economic and financial processes are complex and highly nonlinear. However, somewhat surprisingly, linear models like ARMAXGARCH often describe these processes reasonably well. In this paper, we provide a possible explanation for the empirical success of these models. 1 Formulation of the Problem Economic and financial processes are very complex. It is well know that economic and financial proc...

In this paper, we develop a new accelerated stochastic gradient method for efficiently solving the convex regularized empirical risk minimization problem in mini-batch settings. The use of mini-batches is becoming a golden standard in the machine learning community, because mini-batch settings stabilize the gradient estimate and can easily make good use of parallel computing. The core of our pr...

Despite the increasing research importance of market orientation in the marketing literature, few comparative studies between the European Union and the USA have been conducted. This limits the understanding of marketing orientation strategy in global markets. Investigates the influence of competitive environments on the uses of market orientation in insurance firms in the EU and the USA and th...

Empirical orthogonal function (EOF) analysis has been widely used in meteorology and oceanography to extract dominant modes of behavior in scalar and vector datasets. For analysis of two-dimensional vector fields, such as surface winds or currents, use of the complex EOF method has become widespread. In the present paper, this method is compared with a real-vector EOF method that apparently has...

The following paper draws inspiration from the four national state‐of‐the‐art papers, prepared as part of the ongoing research programme ‘African Perspectives on Human Mobility’. This programme aims to explore alternative conceptions of human mobility based on empirical research in Nigeria, Ghana, Morocco and the Democratic Republic of Congo. The three year programme, co‐ordinated by the Intern...

Given a probability measure P and a reference measure μ, one is often interested in the minimum μ-measure set with P -measure at least α. Minimum volume sets of this type summarize the regions of greatest probability mass of P , and are useful for detecting anomalies and constructing confidence regions. This paper addresses the problem of estimating minimum volume sets based on independent samp...

A general notion of universal consistency of nonparametric estimators is introduced that applies to regression estimation, conditional median estimation, curve fitting, pattern recognition, and learning concepts. General methods for proving consistency of estimators based on minimizing the empirical error are shown. In particular, distribution-free almost sure consistency of neural network esti...

Introduction Review of the progress in any area of inquiry is significant as this assessment enables theory development, identification of trends in topics, funding, and research strategies (Lennon et al. 2001) as well as uncovers future research needs and directions (Damhorst 1990). Several such evaluations have been completed on dress topics including the meanings of dress (Damhorst 1990), th...

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