Almost Sure L(1)-Norm Convergence for Data-Based Histogram Density Estimates.
PITTSBURGH UNIV PA CENTER FOR MULTIVARIATE ANALYSIS
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The main result of this paper is summarized in Theorem 1, which states that when certain conditions of a general nature are satisfied, the data-based histogram density estimator is strongly consistent in the sense that the mean absolute deviation of the estimator and the density function converges to zero almost surely for any density function, as the sample size increases to infinity. Author
- Statistics and Probability