Thirty years ago, the Robin Hood collision resolution strategy was introduced for open addressing hash tables, and a recurrence equation was found for the distribution of its search cost. Although this recurrence could not be solved analytically, it allowed for numerical computations that, remarkably, suggested that the variance of the search cost approached a value of 1.883 when the table was ...

In a predictive model, what is the expected difference in the outcome associated with a unit difference in one of the inputs? In a linear regression model without interactions, this average predictive comparison is simply a regression coefficient (with associated uncertainty). In a model with nonlinearity or interactions, however, the average predictive comparison in general depends on the valu...

Let V be a finite set with q distinct elements. For a subset C of V n, denote var(C) the variance of the average Hamming distance of C. Let T (n,M; q) andR(n,M; q) denote the minimum and maximum variance of the average Hamming distance of subsets of V n with cardinalityM, respectively. In this paper, we study T (n,M; q) and R(n,M; q) for general q. Using methods from coding theory, we derive up...

In order to improve the efficiency and speed of match seeking in fractal compression, this paper presents an Average-Variance function which can make the optimal choice more efficiently. Based on it, we also present a fast optimal choice fractal image compression algorithm and an optimal method of constructing data tree which greatly improve the performances of the algorithm. Analysis and exper...

Rand Corporation, Pittsburgh, PA 15213 e-mail: [email protected] Abstract: Many sufficient dimension reduction methodologies for univariate regression have been extended to multivariate regression. Sliced average variance estimation (SAVE) has the potential to recover more reductive information, and recent development enables us to test the dimension and predictor effects with distributions comm...

In a predictive model, what is the expected change in the outcome associated with a unit change in one of the inputs? In a linear regression model without interactions, this average predictive effect is simply a regression coefficient (with associated uncertainty). In a model with nonlinearity or interactions, however, the average predictive effect in general depends on the values of the predic...

We derive the limiting distribution of the Oaxaca estimator of average treatment effects studied by Kline (2011). A consistent estimator of the asymptotic variance is proposed that makes use of standard regression routines. It is shown that ignoring uncertainty in group means will tend to lead to an overstatement of the asymptotic standard errors. Monte Carlo experiments examine the finite samp...

Questions concerning the properties and quantification of density fluctuations in point patterns continue to provide many theoretical challenges. The purpose of this paper is to characterize certain fundamental aspects of local density fluctuations associated with general point patterns in any space dimension d. Our specific objectives are to study the variance in the number of points contained...

Questions concerning the properties and quantification of density fluctuations in point patterns continues to provide many theoretical challenges. The purpose of this paper is to characterize certain fundamental aspects of local density fluctuations associated with general point patterns in any space dimension d. Our specific objectives are to study the variance in the number of points containe...