cost2_gaussian:
Negative of log posterior associated with the error variance
Description
Calculates the negative of log posterior for the normal error variance, using the leave-one-out cross validated samples.
Usage
cost2_gaussian(x, data_x, data_y, prior_st)
Arguments
x
Log of square bandwidths
data_x
Regressors
data_y
Response variable
prior_st
Another tuning parameter of the prior of error variance, following inverse gamma distribution
Value
Value of the cost function
Details
The prior of normal error variance follows an inverse-gamma distribution with hyperparameter prior_st = 1.
References
X. Zhang and R.D. Brooks and M.L. King (2009), A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation, Journal of Econometrics, 153, 21-32.