One answer to the problem of missing observations in two-way
classification experiments is to insert estimates of missing observations
into deficient cells. Once missing observations have been estimated,
the experimenter may proceed with his analysis using the
familiar normal equations which apply to complete data. This paper
discusses generally the...
This thesis is a study of the problem of calculating the least-squares estimates of the parameters in a linear regression model
when the parameter space is restricted to integer points within a
given polyhedron. General observations are made about estimation
of integer-valued parameters, and an integer-quadratic programming
algorithm is given...
The development of a least squares model for the
determination of compliance constants from various combinations
of vibration frequency, mean square amplitudes
of vibration and centrifugal distortion data is discussed.
The resultant model is applied to frequency and mean square
amplitude data for NO₂ and N₂O₄ and to frequency and...
The two major objectives of this thesis are: (1) demonstrating and
applying optimal design theory by developing an optimal sampling-time
strategy for parameter estimation in stochastic one compartment models,
and (2) examining in depth the extended least squares (ELS) method of
estimating population pharmacokinetic parameters.
The nonlinear weighted least squares...