Albert V Bruno
Biographic Data
| ID | 6101599 |
|---|---|
| NAME | Albert V Bruno |
| GIVEN NAMES | Albert V |
| FAMILY NAME | Bruno |
| SIGNATURE | BRUNO A V |
| AFFILIATIONS | Santa Clara University |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 1975 |
| LATEST PUBLICATION YEAR | 1976 |
| H-INDEX | 0 |
Tgda
A computer program for two-group nonparametric discriminant analysis is described here. Based on Bayes' Theorem for probability revision, the statistical rationale for this program makes use of the calculation of maximum likelihood estimates of group membership. A unique feature of the program is the comparison of the classificatory ability of the Bayesian procedure relative to that of the standard Linear Discriminant Function
Toward Understanding Attitude Structure
This article provides an alternative to the traditional method of selecting one model as representative of the entire population. The authors contend that this procedure extends the usefulness of predictive results and should contribute managerially useful information to research questions which traditionally have been resolved solely through the application of “goodness of fit” effectiveness measures
No prominent works on this page.
Toward Understanding Attitude Structure
This article provides an alternative to the traditional method of selecting one model as representative of the entire population. The authors contend that this procedure extends the usefulness of predictive results and should contribute managerially useful information to research questions which traditionally have been resolved solely through the application of “goodness of fit” effectiveness measures
Tgda
A computer program for two-group nonparametric discriminant analysis is described here. Based on Bayes' Theorem for probability revision, the statistical rationale for this program makes use of the calculation of maximum likelihood estimates of group membership. A unique feature of the program is the comparison of the classificatory ability of the Bayesian procedure relative to that of the standard Linear Discriminant Function
Computer Science (2 works) · Advanced Statistical Methods and Models (1 work) · Artificial Intelligence (1 work) · Artificial Intelligence (1 work) · Bayes' theorem (1 work) · Bayesian probability (1 work) · Discriminant (1 work) · Discriminant function analysis (1 work) · Econometrics (1 work) · Goodness of fit (1 work)