| bbefkr-package | Bayesian bandwidth estimation for the functional kernel regression with unknown error density |
| admkr.cdf | Compute the probability density function and cumulative probability density function of the error, using a global bandwidth of residuals |
| bayMCMC_np_global | Bayesian bandwidth estimation for a functional nonparametric regression with homoscedastic errors |
| bayMCMC_np_local | Bayesian bandwidth estimation for a functional nonparametric regression with homoscedastic errors |
| bayMCMC_semi_global | Bayesian bandwidth estimation for a semi-functional partial linear model |
| bayMCMC_semi_local | Bayesian bandwidth estimation for a semi-functional partial linear model |
| bbefkr | Bayesian bandwidth estimation for the functional kernel regression with unknown error density |
| error.cdfadj | Compute the probability density function and cumulative probability density function of error, using localised bandwidths of residuals |
| error.den | Compute the probability density function and cumulative probability density function of the error, using a global bandwidth of residuals |
| error.denadj | Compute the probability density function and cumulative probability density function of error, using localised bandwidths of residuals |
| fat | Spectroscopy tecator data |
| funopare.kernel | Functional Nadaraya-Watson estimator |
| logdensity_admkr | Compute the marginal likelihood using Chib's (1995) method |
| loglikelihood_global_admkr | Compute the marginal likelihood using Chib's (1995) method |
| loglikelihood_local_admkr | Compute the marginal likelihood using Chib's (1995) method |
| logpriorh2 | Prior density of the squared bandwidth parameters |
| logpriors_admkr | Compute the marginal likelihood using Chib's (1995) method |
| moisture | Spectroscopy tecator data |
| protein | Spectroscopy tecator data |
| SIF | Simulation inefficiency factor |
| simcurve_rough_normerr | Simulated data set |
| simcurve_smooth_normerr | Simulated data set |
| simresp_np_normerr | Simulated data set |
| simresp_semi_normerr | Simulated real-valued predictors in the semi-functional partial linear model |
| simulate_error | Simulate errors |
| specurves | Spectroscopy tecator data |
| tau_normerr | Simulated data set |
| tau_semierr | Simulated real-valued predictors in the semi-functional partial linear model |
| Xvar | Simulated real-valued predictors in the semi-functional partial linear model |