bbemkr (version 1.2)

bbelike: Log likelihood constructed via Gaussian error assumption

Description

Calculate the log likelihood, using the leave-one-out samples.

Usage

bbelike(data_x, data_y, x, sigma, kerntype = c("Gaussian", "Epanechnikov", 
        "Quartic", "Triweight", "Triangular", "Uniform"))

Arguments

data_x

Regressors

data_y

Response variable

x

Log bandwidth of the regressors

sigma

Variance of the error density

kerntype

Type of the kernel function. By default, Gaussian kernel is used.

Value

• Log likelihood value

Details

With the assumption of i.i.d Gaussian error distribution, the likelihood can be constructed and maximized.

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.

See Also

bbeMCMCrecording