It is important to understand the dynamics of malaria vectors in implementing malaria control strategies. Six villages were selected from different sections in the Three Gorges Reservoir for exploring the relationship between the climatic factors and its malaria vector density from 1997 to 2007 using the auto-regressive linear model regression method. The result indicated that both temperature ...

Price stability has been the foremost task of monetary policy. The information relating to the response of prices to monetary policy shocks is essential for conducting monetary policy in general and for inflation targeting of central banks in particular. Most of the published empirical studies analyze the response of an aggregate price index like CPI or a consumption deflator and their r...

Nonlinear kernels are used extensively in regression models in statistics and machine learning since they often improve predictive accuracy. Variable selection is a challenge in the context of kernel based regression models. In linear regression the concept of an effect size for the regression coefficients is very useful for variable selection. In this paper we provide an analog for the effect ...

Models based on economic theory have serious problems at forecasting exchange rates better than simple univariate driftless random walk models, especially at short horizons. Multivariate time series models suffer from the same problem. In this paper, we propose to forecast exchange rates with a large Bayesian VAR (BVAR), using a panel of 33 exchange rates vis-a-vis the US Dollar. Since exchange...

The increasing quality and affordability of consumer electroencephalogram (EEG) headsets make them attractive for situations where medical grade devices are impractical. Predicting and tracking cognitive states is possible for tasks that were previously not conducive to EEG monitoring. For instance, monitoring operators for states inappropriate to the task (e.g. drowsy drivers), tracking mental...

In this paper we present a simple hierarchical Bayesian treatment of the sparse kernel logistic regression (KLR) model based MacKay’s evidence approximation. The model is re-parameterised such that an isotropic Gaussian prior over parameters in the kernel induced feature space is replaced by an isotropic Gaussian prior over the transformed parameters, facilitating a Bayesian analysis using stan...

Natural language processing is an interdisciplinary field of research which studies the problems and possibilities of automated generation and understanding of natural human languages. Text categorization is a central subfield of natural language processing. Automatically assigning categories to digital texts has a wide range of applications in today’s information society—from filtering spam to...