2 resultados para Basic hypergeometric functions
em DigitalCommons@The Texas Medical Center
Resumo:
This descriptive cross-sectional survey compared the perceptions of public health nursing practitioners, educators and administrators along two dimensions: the importance of community-focused functions in public health nursing and which occupational categories in public health are responsible for those functions. More than 50 percent of the mailed questionnaires that were sent to a systematic stratified nationwide sample of public health nurses were returned. In general, respondents: were female, were in their 40s, received their basic nursing education in baccalaureate programs, had either a baccalaureate or a master's degree, worked in official agencies or schools, and had approximately 14 years of experience in public health with six in their present position.^ Significant differences between practitioners, educators and administrators were found in their perceptions of both the importance of community-focused functions in public health nursing and in which occupational category they indicated as having the major responsibility to perform those functions. Educators and administrators perceived community-focused functions as more important than did practitioners. Overall the occupational category of administrator was indicated as having the major responsibility for performing community-focused functions.^
Resumo:
A large number of ridge regression estimators have been proposed and used with little knowledge of their true distributions. Because of this lack of knowledge, these estimators cannot be used to test hypotheses or to form confidence intervals.^ This paper presents a basic technique for deriving the exact distribution functions for a class of generalized ridge estimators. The technique is applied to five prominent generalized ridge estimators. Graphs of the resulting distribution functions are presented. The actual behavior of these estimators is found to be considerably different than the behavior which is generally assumed for ridge estimators.^ This paper also uses the derived distributions to examine the mean squared error properties of the estimators. A technique for developing confidence intervals based on the generalized ridge estimators is also presented. ^