Nonparametric kernel smoothing methods for mixed data types

Documentation for package `np' version 0.30-3

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-- B --

bw	Cross Country Growth Panel
bw.all	Cross-Sectional Data on Wages
bw.subset	Cross-Sectional Data on Wages

-- C --

Canadian High School Graduate Earnings

-- G --

Extract Gradients

-- I --

Italian GDP Panel

-- N --

np	Nonparametric Kernel Smoothing Methods for Mixed Data Types
npcdens	Kernel Conditional Density and Distribution Estimates with Mixed Data Types
npcdensbw	Kernel Conditional Density Bandwidth Selection with Mixed Data Types
npcdist	Kernel Conditional Density and Distribution Estimates with Mixed Data Types
npcmstest	Kernel Consistent Model Specification Test with Mixed Data Types
npconmode	Kernel Modal Regression with Mixed Data Types
npindex	Semiparametric Single Index Model
npindexbw	Semiparametric Single Index Model Parameter and Bandwidth Selection
npksum	Kernel Sums with Mixed Data Types
npplot	General Purpose Plotting of Nonparametric Objects
npplreg	Partially Linear Kernel Regression with Mixed Data Types
npplregbw	Partially Linear Kernel Regression Bandwidth Selection with Mixed Data Types
npqcmstest	Kernel Consistent Quantile Regression Model Specification Test with Mixed Data Types
npqreg	Kernel Quantile Regression with Mixed Data Types
npreg	Kernel Regression with Mixed Data Types
npregbw	Kernel Regression Bandwidth Selection with Mixed Data Types
npscoef	Smooth Coefficient Kernel Regression
npscoefbw	Smooth Coefficient Kernel Regression Bandwidth Selection
npseed	Set Random Seed
npsigtest	Kernel Regression Significance Test with Mixed Data Types
npudens	Kernel Density and Distribution Estimation with Mixed Data Types
npudensbw	Kernel Density Bandwidth Selection with Mixed Data Types
npudist	Kernel Density and Distribution Estimation with Mixed Data Types

-- O --

Cross Country Growth Panel

-- S --

se	Extract Standard Errors

-- U --

Compute Quantiles

-- W --

Cross-Sectional Data on Wages