Abstract
Let (X1,Y1),...(Xn,Yn) be a random sample from the (k+1)-dimensional multivariate density functionf*(x,y). Estimates of thek-dimensional density functionf(x)=∫f*(x,y)dy of the form
are considered whereW(x) is a bounded, nonnegative weight function andb1(n),...,bk(n) and bandwidth sequences depending on the sample size and tending to 0 asn→∞. For the regression function
whereh(x)=∫y(f)*(x, y)dy , estimates of the form
are considered. In particular, unform consistency of the estimates is obtained by showing that\(||\hat f_n (x) - f(x)||_\infty \) and\(||\hat m_n (x) - m(x)||_\infty \) converge completely to zero for a large class of “good” weight functions and under mild conditions on the bandwidth sequencesbk(n)'s.
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Research supported by National Institute of Environmental Health Sciences Under Grant 5T32 ES07011.
For this author, revisions made while supported by the Air Force Office of Scientific Research under Contract Number F49620-79-C-0140.
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Cheng, K.F., Taylor, R.L. On the uniform complete convergence of estimates for multivariate density functions and regression curves. Ann Inst Stat Math 32, 187–199 (1980). https://doi.org/10.1007/BF02480324
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DOI: https://doi.org/10.1007/BF02480324