Description Usage Arguments Value Author(s) References
Determines the LP basis for a given parametric prior distribution.
1 | gLP.basis(x, g.par, m, con.prior, ind)
|
x |
|
g.par |
Estimated parameters for specified prior distribution (i.e beta prior: α and β; normal prior: μ and τ^2; gamma prior: α and β). |
m |
Number of LP-Polynomial basis. |
con.prior |
Specified conjugate prior distribution for basis functions. Options are |
ind |
Default is NULL which returns matrix with m columns that consists of LP-basis functions; user can provide a specific choice through |
Matrix with m
columns of values for the LP-Basis functions evaluated at x
-values.
Subhadeep Mukhopadhyay, Doug Fletcher
Mukhopadhyay, S. and Fletcher, D., 2018. "Generalized Empirical Bayes via Frequentist Goodness of Fit," Nature Scientific Reports, 8(1), p.9983, https://www.nature.com/articles/s41598-018-28130-5.
Mukhopadhyay, S., 2017. "Large-Scale Mode Identification and Data-Driven Sciences," Electronic Journal of Statistics, 11(1), pp.215-240.
Mukhopadhyay, S. and Parzen, E., 2014. "LP Approach to Statistical Modeling," arXiv: 1405.2601.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.