A Bias Bound Approach to Non-Parametric Inference

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Documentation for package ‘rbbnp’ version 1.1.0

• DESCRIPTION file
• User guides, package vignettes and other documentation
• Package NEWS
• Package README

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