Computing of high breakdown regression estimators without sorting on graphics processing units

We present an approach to computing high-breakdown regression estimators in parallel on graphics processing units (GPU).We show that sorting the residuals is not necessary, and it can be substituted by calculating the median. We present and compare various methods to calculate the median and order statistics on GPUs. We introduce an alternative method based on the optimization of a convex function, and showits numerical superiority when calculating the order statistics of very large arrays on GPUs.

Influence functions of two families of robust estimators under proportional scatter matrices

In this paper, under a proportional model, two families of robust estimates for the proportionality constants, the common principal axes and their size are discussed. The first approach is obtained by plugging robust scatter matrices on the maximum likelihood equations for normal data. A projection- pursuit and a modified projection-pursuit approach, adapted to the proportional setting, are also considered. For all families of estimates, partial influence functions are obtained and asymptotic variances are derived from them. The performance of the estimates is compared through a Monte Carlo study. © 2006 Springer-Verlag.

Robust plug-in estimators in proportional scatter models

We address the problem of estimating the principal axes and their size in the case of several populations under the assumption of a proportional model. We propose robust estimators for the common principal axes and their size. The robust estimators are based on asymptotically normal and equivariant robust scatter estimators. The asymptotic distribution of the robust estimators including the proportionality constants are derived. © 2003 Elsevier B.V. All rights reserved.

Selected Ranked Set Sampling

This paper proposes a sampling procedure called selected ranked set sampling (SRSS), in which only selected observations from a ranked set sample (RSS) are measured. This paper describes the optimal linear estimation of location and scale parameters based on SRSS, and for some distributions it presents the required tables for optimal selections. For these distributions, the optimal SRSS estimators are compared with the other popular simple random sample (SRS) and RSS estimators. In every situation the estimators based on SRSS are found advantageous at least in some respect, compared to those obtained from SRS or RSS. The SRSS method with errors in ranking is also described. The relative precision of the estimator of the population mean is investigated for different degrees of correlations between the actual and erroneous ranking. The paper reports the minimum value of the correlation coefficient between the actual and the erroneous ranking required for achieving better precision with respect to the usual SRS estimator and with respect to the RSS estimator.

Prediction error property of the Lasso Estimator and its generalization

The lasso procedure is an estimator-shrinkage and variable selection method. This paper shows that there always exists an interval of tuning parameter values such that the corresponding mean squared prediction error for the lasso estimator is smaller than for the ordinary least squares estimator. For an estimator satisfying some condition such as unbiasedness, the paper defines the corresponding generalized lasso estimator. Its mean squared prediction error is shown to be smaller than that of the estimator for values of the tuning parameter in some interval. This implies that all unbiased estimators are not admissible. Simulation results for five models support the theoretical results.

The effect of private school competition on public school performance in Georgia

This article presents estimates of the effect of private school competition on public school performance. Using data on school districts in Georgia, the authors estimate models relating tenth- and third-grade test scores for either reading or mathematics to the level of private school competition. Test scores are not measurably or significantly higher in areas with greater private school competition, a result robust through multiple estimations using three measures of private school competition and a variety of control variables. The authors address the possible endogeneity between test scores and private school competition using instrumental variables estimators, with percentage of the population that is Catholic, county population in 1980, lagged competition, and various other measures as alternative instruments.

Robust parallel filtering for mobile agent tracking

In this paper we develop a robust method of target/mobile agent tracking involving two independent estimators with separate measurement systems. The outputs of the two estimators are combined using simple trigonometry (post-estimation data fusion) and provide a robust and reliable tracking path. We demonstrate that through the use of recent advances in robust set-value state estimation, our robust parallel filter approach performs well even when the individual filters do not. Brief comparisons with common data fusion methods are conducted in order to demonstrate the advantages of our parallel (post-estimation fusion) approach

Democracy and economic growth : a meta-analysis

Despite a sizeable theoretical and empirical literature, no firm conclusions have been drawn regarding the impact of political democracy on economic growth. This article challenges the consensus of an inconclusive relationship through a quantitative assessment of the democracy-growth literature. It applies meta-regression analysis to the population of 483 estimates derived from 84 studies on democracy and growth. Using traditional meta-analysis estimators, the bootstrap, and Fixed and Random Effects meta-regression models, it derives several robust conclusions. Taking all the available published evidence together, it concludes that democracy does not have a direct impact on economic growth. However, democracy has robust, significant, and positive indirect effects through higher human capital, lower inflation, lower political instability, and higher levels of economic freedom. Democracies may also be associated with larger governments and less free international trade. There also appear to be country- and region-specific democracy-growth effects. Overall, democracy's net effect on the economy does not seem to be detrimental.

A test of the Wagner's hypothesis for the Fiji Islands

In this article we examine Wagner's law for Fiji for the period 1970 to 2002. Using the Johansen (1988) test for cointegration, we find one cointegration relationship between national output and government expenditure. Using five different long run estimators, we find robust results on the impact of national income on government expenditure. The elasticity ranges from 1.36 to 1.44, implying that a 1% increase in income leads to a 1.36-1.44% increase in government expenditure. Moreover, we find that in the long run national income Granger causes government expenditure. While these results are consistent with Wagner's law, we warn policy makers that because Fiji's total debt stands at around 69% of GDP, in future the bulk of expenditure will go towards debt financing at the expense of productive sectors.

Modelling the relationship between defense spending and economic growth for the Fiji Islands

The goal of this paper is to examine the nexus between GDP and military expenditure. We model this relationship within a multivariate framework by including exports in the model. We use the recently developed bounds testing approach to cointegration and find that there is a long run relationship among the variables when GDP is the endogenous variable. Normalizing on GDP and using four different estimators, we find that in the long run both military expenditure and exports have a positive impact on GDP. Finally, using the Granger causality test, we find that there is evidence for military expenditure Granger causing exports and exports Granger causing GDP, implying that military expenditure indirectly Granger causes GDP in the short run. In the long run, we find that both military expenditure and exports Granger cause GDP for Fiji. Our findings are consistent with the Keynesian school of thought, leading us to derive some policy implications.

Earthquake fatalities : the interaction of nature and political economy

To say that the level of fatalities resulting from an earthquake is inversely related to a country's per capita level of income is hardly novel. What makes our approach novel is that we relate fatalities to both per capita income and the level of inequality that exists within a country through their joint impact on the likelihood of collective action being taken to mitigate the destructive potential of quakes. We first develop a theoretical model which offers an explanation as to why, in some environments, different segments of society prove incapable of arriving at what all parties perceive to be an agreeable distribution of the burden of the necessary collective action, causing the relatively wealthy simply to self-insure against the disaster while leaving the relatively poor to its mercy. Following this, we test our theoretical model by evaluating 269 large earthquakes occurring worldwide, between 1960 and 2002, taking into account other factors that influence a quake's destructiveness such as its magnitude, depth and proximity to population centers. Using a Negative Binomial estimation strategy with both random and fixed estimators, we find strong evidence of the theoretical model's predictions. That is, while earthquakes themselves are natural phenomena beyond the reach of humankind, our collective inaction with respect to items like the creation and enforcement of building codes, failure to retrofit structures and to enact quake-sensitive zoning clearly plays a part in determining the actual toll that a given quake takes. And, it is through these and other examples of collective inaction that limited per capita income and inequality couple together with a given quake's natural destructive power in determining the actual fatalities resulting from a quake.

The allocation of development aid assistance : do new donors have old motives?

The aid allocation literature explores the motives behind development aid  assistance. This literature is enormous, yet surprisingly, the extant empirical  studies have in the main only focused on the motives of established donors. Consequently, relatively little is known of the motives of new donors. This paper explores the aid allocation motives of three relatively new DAC donors: Greece, Luxembourg, and Portugal. Both OLS and Tobit two-way effects estimators are used to model their aid allocation process. The results indicate that humanitarian concerns are not an important factor for these three donors. Greece contributes aid predominately to its neighbors and to transitional East European nations. Portugal is motivated by commercial interests and former colony status. The bandwagon effect exists in reverse for Portugal. Commercial interests operate also for Luxembourg. Additionally, Luxembourg appears to donate to smaller more developed countries and is less inclined to donate to East European nations.

Simultaneous volatility transmission and spillover effects

Simultaneous volatility models are developed and shown to be separate from multivariate GARCH estimators. An example is provided that allows for simultaneous and unidirectional volatility and volume of trade effects. These effects are tested using intraday data from the Australian cash index and index futures markets. Overnight volatility spillover effects from the United States S&P500 index futures markets are tested using alternative estimates of this US market volatility. The simultaneous volatility model proves to be robust to alternative specifications of returns equations and to misspecification of the direction of volatility causality.

A state space based approach in non-linear hemodynamic response modeling with fMRI data

In this paper we use the modified and integrated version of the balloon model in the analysis of fMRI data. We propose a new state space model realization for this balloon model and represent it with the standard A,B,C and D matrices widely used in system theory. A second order Padé approximation with equal numerator and denominator degree is used for the time delay approximation in the modeling of the cerebral blood flow. The results obtained through numerical solutions showed that the new state space model realization is in close agreement to the actual modified and integrated version of the balloon model. This new system theoretic formulation is likely to open doors to a novel way of analyzing fMRI data with real time robust estimators. With further development and validation, the new model has the potential to devise a generalized measure to make a significant contribution to improve the diagnosis and treatment of clinical scenarios where the brain functioning get altered. Concepts from system theory can readily be used in the analysis of fMRI data and the subsequent synthesis of filters and estimators.