All the animals are gone? The politics of contemporary hunter arcade games.

Recent proliferation and popularity of personal computer and console games has meant that scholarship around video arcade games has been largely ignored. Arcade games had their halcyon days during the 1970s and 1980s when 'Space Invaders', 'Pong' and 'Donkey Kong' were household names. The inception of scholarship into games occurred in the 1990s; a time when arcade games were writ small in the cultural imagination, at least compared to the newer home computer and video games. Thus in games theory they are typically discussed only in terms of their role as antecedents to their more popular kin. Moreover, they seem innocuous because they are so publicly accessible. Against this assumption, and lack of scholarship, this paper explores a selection of contemporary arcade games which we describe as 'hunting' games. Arcade hunting games are first-person shooter (FPS) involving one or more players shooting simulated wild animals. They are commonly situated in cinema foyers, hotels, and family entertainment centres. However, despite a presumption of institutional moderation afforded by the public accessibility of these spaces, this paper argues that this genre works through a range of political modalities that require more scholarly consideration than currently given.

Fast cross-validation of kernel fisher discriminant classifiers

Given n training examples, the training of a Kernel Fisher Discriminant (KFD) classifier corresponds to solving a linear system of dimension n. In cross-validating KFD, the training examples are split into 2 distinct subsets for a number of times (L) wherein a subset of m examples is used for validation and the other subset of(n - m) examples is used for training the classifier. In this case L linear systems of dimension (n - m) need to be solved. We propose a novel method for cross-validation of KFD in which instead of solving L linear systems of dimension (n - m), we compute the inverse of an n × n matrix and solve L linear systems of dimension 2m, thereby reducing the complexity when L is large and/or m is small. For typical 10-fold and leave-one-out cross-validations, the proposed algorithm is approximately 4 and (^4/9n) times respectively as efficient as the naive implementations. Simulations are provided to demonstrate the efficiency of the proposed algorithms.

Panel cointegration tests of the Fisher effect

Most empirical evidence suggests that the Fisher effect, stating that inflation and nominal interest rates should cointegrate with a unit slope on inflation, does not hold, a finding at odds with many theoretical models. This paper argues that these results can be attributed in part to the low power of univariate tests, and that the use of panel data can generate more powerful tests. For this purpose, we propose two new panel cointegration tests that can be applied under very general conditions, and that are shown by simulation to be more powerful than other existing tests. These tests are applied to a panel of quarterly data covering 20 OECD countries between 1980 and 2004. The evidence suggest that the Fisher effect cannot be rejected once the panel evidence on cointegration has been taken into account. Copyright © 2008 John Wiley & Sons, Ltd.

Panel cointegration tests of the Fisher hypothesis

Recent empirical studies suggest that the Fisher hypothesis, stating that inflation and nominal interest rates should cointegrate with a unit parameter on inflation, does not hold, a finding at odds with many theoretical models. This paper argues that these results can be explained in part by the low power inherent in univariate cointegration tests and that the use of panel data should generate more powerful tests. In doing so, we propose two new panel cointegration tests, which are shown by simulation to be more powerful than other existing tests. Applying these tests to a panel of monthly data covering the period 1980:1 to 1999:12 on 14 OECD countries, we find evidence supportive of the Fisher hypothesis.