A Bias Bound Approach to Non-Parametric Inference

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Documentation for package ‘rbbnp’ version 0.1.0

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biasBound_condExpectation Bias bound approach for conditional expectation estimation
biasBound_density Bias bound approach for density estimation
DATA_PATH The Path to the Data Folder
epanechnikov_kernel Epanechnikov Kernel
epanechnikov_kernel_ft Fourier Transform Epanechnikov Kernel
EXT_DATA_PATH The Path to the External Data Folder for Non-R Data Files
fun_approx Approximation Function for Intensive Calculations
gen_sample_data Generate Sample Data
get_avg_f1x Kernel point estimation
get_avg_fyx Kernel point estimation
get_avg_phi Compute Sample Average of Fourier Transform Magnitude
get_avg_phi_log Compute log sample average of fourier transform and get mod
get_conditional_var get the conditional variance of Y on X for given x
get_est_Ar get the estimation of A and r
get_est_B get the estimation of B
get_est_b1x Estimation of bias b1x
get_est_byx Estimation of bias byx
get_est_vy get the estimation of Vy
get_sigma Estimation of sigma
get_sigma_yx Estimation of sigma_yx
get_xi_interval get xi interval
kernel_reg Kernel Regression function
normal_kernel Normal Kernel Function
normal_kernel_ft Fourier Transform of Normal Kernel
plot_ft Plot the Fourier Transform
rpoly01 Generate n samples from the distribution
sample_data Sample Data
sinc Infinite Kernel Function
sinc_ft Define the closed form FT of the infinite order kernel sin(x)/(pi*x)
true_density_2fold True density of 2-fold uniform distribution
W_kernel Define the inverse Fourier transform function of W
W_kernel_ft Define the Fourier transform of a infinite kernel proposed in Schennach 2004