| Compute Optimal Block Length for Stationary and Circular Bootstrap | b.star |
| Canadian High School Graduate Earnings | cps71 |
| Local-Polynomial Basis Dimension Helper | dimBS |
| 1995 British Family Expenditure Survey | Engel95 |
| Extract Gradients | gradients gradients.condensity gradients.condistribution gradients.npregression gradients.qregression gradients.singleindex |
| Italian GDP Panel | Italy |
| Nonparametric Kernel Smoothing Methods for Mixed Data Types | np-package np |
| Validated plot control helpers | np_boot_control np_grid_control np_render_control |
| Kernel Functions Used In 'np' | np.kernels |
| Global Package Options for 'np' | np.options |
| Cross-Validated Pairs Plot (Helper Functions) | np.pairs np.pairs.plot |
| Kernel Conditional Density Estimation with Mixed Data Types | npcdens npcdens.conbandwidth npcdens.default npcdens.formula |
| Kernel Conditional Density Bandwidth Selection with Mixed Data Types | npcdensbw npcdensbw.conbandwidth npcdensbw.default npcdensbw.formula |
| Conditional Density Hat Operator | npcdenshat |
| Kernel Conditional Distribution Estimation with Mixed Data Types | npcdist npcdist.condbandwidth npcdist.default npcdist.formula |
| Kernel Conditional Distribution Bandwidth Selection with Mixed Data Types | npcdistbw npcdistbw.condbandwidth npcdistbw.default npcdistbw.formula |
| Conditional Distribution Hat Operator | npcdisthat |
| Kernel Consistent Model Specification Test with Mixed Data Types | npcmstest |
| Kernel Modal Regression with Mixed Data Types | npconmode npconmode.conbandwidth npconmode.default npconmode.formula plot.conmode predict.conmode |
| Kernel Copula Estimation with Mixed Data Types | as.data.frame.npcopula fitted.npcopula npcopula npcopula.default npcopula.formula plot.npcopula predict.npcopula print.npcopula se.npcopula summary.npcopula |
| Kernel Consistent Density Equality Test with Mixed Data Types | npdeneqtest |
| Kernel Consistent Pairwise Nonlinear Dependence Test for Univariate Processes | npdeptest |
| Semiparametric Single Index Model | npindex npindex.default npindex.formula npindex.sibandwidth |
| Semiparametric Single Index Model Parameter and Bandwidth Selection | npindexbw npindexbw.default npindexbw.formula npindexbw.sibandwidth |
| Kernel Sums with Mixed Data Types | npksum npksum.default npksum.formula npksum.numeric |
| Location-Scale Kernel Quantile Regression with Mixed Data Types | fitted.lsqregression gradients.lsqregression nplsqreg nplsqreg.default nplsqreg.formula nplsqreg.lsqregressionbandwidth plot.lsqregression predict.lsqregression print.lsqregression quantile.lsqregression residuals.lsqregression se.lsqregression summary.lsqregression |
| Bandwidth Selection for Location-Scale Kernel Quantile Regression | lsqregressionbandwidth nplsqregbw nplsqregbw.default nplsqregbw.formula nplsqregbw.lsqregressionbandwidth print.lsqregressionbandwidth summary.lsqregressionbandwidth |
| Partially Linear Kernel Regression with Mixed Data Types | npplreg npplreg.default npplreg.formula npplreg.plbandwidth |
| Partially Linear Kernel Regression Bandwidth Selection with Mixed Data Types | npplregbw npplregbw.default npplregbw.formula npplregbw.plbandwidth |
| Kernel Consistent Quantile Regression Model Specification Test with Mixed Data Types | npqcmstest |
| Kernel Quantile Regression with Mixed Data Types | npqreg npqreg.condbandwidth npqreg.default npqreg.formula plot.qregression predict.qregression |
| Kernel Univariate Quantile Estimation | npquantile |
| Kernel Regression with Mixed Data Types | npreg npreg.default npreg.formula npreg.rbandwidth |
| Kernel Regression Bandwidth Selection with Mixed Data Types | npregbw npregbw.default npregbw.formula npregbw.rbandwidth |
| Nonparametric Regression Hat Operator | npreghat npreghat.formula npreghat.npregression npreghat.rbandwidth predict.npreghat print.npreghat |
| Nonparametric Instrumental Regression | npregiv |
| Nonparametric Instrumental Derivatives | npregivderiv |
| Smooth Coefficient Kernel Regression | npscoef npscoef.default npscoef.formula npscoef.scbandwidth |
| Smooth Coefficient Kernel Regression Bandwidth Selection | npscoefbw npscoefbw.default npscoefbw.formula npscoefbw.scbandwidth |
| Kernel Consistent Serial Dependence Test for Univariate Nonlinear Processes | npsdeptest |
| Set Random Seed | npseed |
| Experimental Hat Operators for Semiparametric Estimators | npindexhat npplreghat npscoefhat |
| Kernel Regression Significance Test with Mixed Data Types | npsigtest npsigtest.default npsigtest.formula npsigtest.npregression npsigtest.rbandwidth |
| Kernel Consistent Density Asymmetry Test with Mixed Data Types | npsymtest |
| Truncated Second-order Gaussian Kernels | nptgauss |
| Kernel Density Estimation with Mixed Data Types | npudens npudens.bandwidth npudens.default npudens.formula |
| Kernel Density Bandwidth Selection with Mixed Data Types | npudensbw npudensbw.bandwidth npudensbw.default npudensbw.formula |
| Unconditional Density Hat Operator | npudenshat |
| Kernel Distribution Estimation with Mixed Data Types | npudist npudist.dbandwidth npudist.default npudist.formula |
| Kernel Distribution Bandwidth Selection with Mixed Data Types | npudistbw npudistbw.dbandwidth npudistbw.default npudistbw.formula |
| Unconditional Distribution Hat Operator | npudisthat |
| Kernel Bounded Univariate Density Estimation Via Boundary Kernel Functions | npuniden.boundary |
| Kernel Bounded Univariate Density Estimation Via Data-Reflection | npuniden.reflect |
| Kernel Shape Constrained Bounded Univariate Density Estimation | npuniden.sc |
| Kernel Consistent Univariate Density Equality Test with Mixed Data Types | npunitest |
| Cross Country Growth Panel | bw oecdpanel |
| General Purpose Plotting of Nonparametric Objects | plot.bandwidth plot.conbandwidth plot.np plot.plbandwidth plot.rbandwidth plot.scbandwidth plot.sibandwidth |
| Extract Standard Errors | se |
| Compute Quantiles | uocquantile |
| Cross-Sectional Data on Wages | bw.all bw.subset wage1 |