ON MULTIVARIATE KERNEL ESTIMATION FOR SAMPLES FROM WEIGHTED DISTRIBUTIONS

Data from multivariate weighted distributions appear in such cases as missing data, damaged data, sociological or economic data. Multivariate kernel density estimation is discussed for these data where its mean square error (pointwise and integrated) is derived and for an important and common special case, its mean absolute error is outlined. The analogous problem dealing with regression estimation is presented.