R: A Bias Bound Approach to Non-Parametric Inference

# A Bias Bound Approach to Non-Parametric Inference

## Documentation for package ‘rbbnp’ version 1.1.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

biasBound_condExpectation | Bias bound approach for conditional expectation estimation
biasBound_density | Bias bound approach for density estimation
coef.bbnp_density | Extract Coefficients from bbnp_density Object
coef.bbnp_regression | Extract Coefficients from bbnp_regression Object
confint.bbnp_density | Extract Confidence Intervals from bbnp_density Object
confint.bbnp_regression | Extract Confidence Intervals from bbnp_regression Object
create_biasBound_config | Create a configuration object for bias bound estimations
create_kernel_functions | Create kernel functions based on configuration
cv_bandwidth | Cross-Validation for Bandwidth Selection
fitted.bbnp_regression | Extract Fitted Values from bbnp_regression Object
gen_sample_data | Generate Sample Data
plot.bbnp_density | Plot Method for bbnp_density Objects
plot.bbnp_regression | Plot Method for bbnp_regression Objects
print.bbnp_density | Print Method for bbnp_density Objects
print.bbnp_regression | Print Method for bbnp_regression Objects
sample_data | Sample Data
select_bandwidth | Select Optimal Bandwidth
silverman_bandwidth | Silverman's Rule of Thumb for Bandwidth Selection
summary.bbnp_density | Summary Method for bbnp_density Objects
summary.bbnp_regression | Summary Method for bbnp_regression Objects