Boundedly complete families which are not complete

Summary Completeness of a family of probability distributions implies its bounded completeness but not conversely. An example of a family which is boundedly complete but not complete was presented by Lehmann and Scheffe [5]. This appears to be the only such example quoted in the statistical literature. The purpose of this note is to provide further examples of this type. It is shown that any given family of power series distributions can be used to construct a class containing infinitely many boundedly complete, but not complete, families. Furthermore, it is shown that the family of continuous distributions , is boundedly complete, but not complete, whereU denotes the uniform distribution on [a, b] and {P _ϑ,ϑ ∈ IR}, is a translation family generated by a distributionP ₀ with mean value zero, which is continuous with respect to the Lebesgue measure.     

Agricultural practices in Eastern Maputaland

The various agricultural practices employed in eastern Maputaland are described.

Agricultural strategies utilized in Maputaland are low in productivity but aim to minimize risk. The area is marginal for agriculture as soils are sandy and rainfall unreliable. Insects and plant diseases accentuate the problem. Infrastructure is lacking in the area. Traditional agricultural systems predominate.

Farming in the area is generally of a subsistence nature and can be divided into gardening, swamp farming and field cropping. Steps towards modernization of agriculture must take into account all existing constraints.     

Projecting the future size and health status of the U.S. elderly population

"A projection model based on a multivariate continuous state, stochastic process is presented. The model allows multiple time-varying covariates to be used so parameters can be estimated from time series information on health changes and mortality, and their interaction. Health changes are simulated by altering parameters controlling the age trajectory and diffusion of risk factor means, variances, and covariances....By increasing the information used in projections it may be possible to better (a) anticipate the state of health at extreme ages, (b) forecast changes in health at specific ages over time, (c) stimulate the effects of specific interventions, and (d) determine the sensitivity of outcomes to a range of interventions."     

Maximizing purchase decision factors other than price

Assessing and acquiring technology does not have to be chaotic, driven solely by price, clinical preference, and emotion. With the tools available, it can be distilled to a process of organized common sense, which results in maximum flexibility for the user and allows materiel managers to procure the best, most cost-effective equipment for the hospital.     

How to handle donor complaints

Responding to donor complaints takes great care. But know who's complaining and keep things in perspective.