Name
Abstract | ||
|---|---|---|
The implementation of Bayesian predictive procedures under standard normal models is considered. Two distributions are of particular interest, the K-prime and K-square distributions. They also give exact inferences for simple and multiple correlation coefficients. Their cumulative distribution functions can be expressed in terms of infinite series of multiples of incomplete beta function ratios, thus adequate for recursive calculations. Efficient algorithms are provided. To deal with special cases where possible underflows may prevent a recurrence to work properly, a simple solution is proposed which results in a procedure which is intermediate between two classes of algorithm. Some examples of applications are given. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.csda.2008.11.004 | Computational Statistics & Data Analysis |
Keywords | Field | DocType |
k-square distribution,exact inference,multiple correlation coefficient,infinite series,implementing bayesian predictive procedure,efficient algorithm,incomplete beta function,incomplete beta function ratio,particular interest,simple solution,cumulative distribution function,bayesian approach,bayesian predictive procedure,predictive distribution | Prime (order theory),Econometrics,Multiple correlation,Beta function,Series (mathematics),Recurrence relation,Cumulative distribution function,Standard normal table,Statistics,Mathematics,Bayesian probability | Journal |
Volume | Issue | ISSN |
54 | 3 | Computational Statistics and Data Analysis |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jacques Poitevineau | 1 | 0 | 1.35 |
| Bruno Lecoutre | 2 | 0 | 1.69 |