ESTIMATION OF PARAMETERS FROM INCOMPLETE DATA

Maximum likelihood estimators are found for the parameters of a normal trivariate population in the case where observations on one variable are missing from part of the data and observations on another variable are missing from the remainder of the data. Results are presented showing the amount of additional information obtained by these maximum likelihood methods, which make optimum use of the fragmentary data. She formulas derived may also be applied to fragmentary bivariate data.