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AMS 1980 subject classification: primary 62G05. secondary 62G20. Abstract: Kernel density estimators are used for the estimation of integrals of various squared derivatives of a probability density. Rates of convergence in mean squared error are calculated, which show that appropriate values of the smoothing parameter are much smaller than those for(More)
Many practical problems, especially some connected with forecasting , require nonparametric estimation of conditional densities from mixed data. For example, given an explanatory data vector X for a prospective customer, with components that could include the customer's salary, occupation, age, sex, marital status and address, a company might wish to(More)
The accuracy of the binned kernel density estimator is studied for general binning rules. We derive mean squared error results for the closeness of this estimator to both the true density and the unbinned kernel estimator. The binning rule and smoothness of the kernel function are shown to innuence the accuracy of the binned kernel estimators. Our results(More)
It is shown that bagging, a computationally intensive method, asymptotically improves the performance of nearest neighbour classifiers provided that the resample size is less than 69% of the actual sample size, in the case of with-replacement bagging, or less than 50% of the sample size, for without-replacement bagging. However, for larger sampling(More)
It is well known that the number of modes of a kernel density estimator is monotone nonincreasing in the bandwidth if the kernel is a Gaussian density. There is numerical evidence of nonmonotonic-ity in the case of some non-Gaussian kernels, but little additional information is available. The present paper provides theoretical and numerical descriptions of(More)
In this paper we consider a nonparametric regression model which admits a mix of continuous and discrete regressors, some of which may in fact be redundant (i.e., irrelevant). We show that, asymptoti-cally, a data-driven least squares cross-validation method can remove irrelevant regressors. Simulations reveal that this 'automatic dimensionality reduction'(More)
  • Andrew Moravcsik, Anne-Marie Burley, James Caporaso, David Dessler, Geoffrey Garrett, Peter Gourevitch +14 others
  • 2008
The European Community (EC) is experiencing its most important period of reform since the completion of the Common Market in 1968. This new impulse toward European integration-the "relaunching" of Europe, the French call it-was unexpected. The late 1970s and early 1980s were periods of "Europessimism" and "Eurosclerosis," when politicians and academics(More)
1. Introduction and overview of living wage ordinances 5 Purpose of this report 5 The Oakland Living Wage Ordinance in national perspective 6 Oakland's wage standard and coverage 7 2. Recent growth and income distribution trends in Oakland 9 Economic growth in Oakland 9 Those left behind 9 3. Employment and pay at the Port of Oakland 11 The Port's(More)