Parallel Nonparametric Kernel Smoothing Methods for Mixed Data
Types Using 'MPI'
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Documentation for package ‘npRmpi’ version 0.70-2
- DESCRIPTION file
- User guides, package vignettes and other documentation
- Code demos. Use demo() to run them.
- Package NEWS
- Package README
Help Pages
A B C D E F G I L M N O P S T U W
| npRmpi-package | Parallel Nonparametric Kernel Smoothing Methods for Mixed Data Types |
-- A --
| as.data.frame.npcopula | Kernel Copula Estimation with Mixed Data Types |
-- B --
| b.star | Compute Optimal Block Length for Stationary and Circular Bootstrap |
| bw | Cross Country Growth Panel |
| bw.all | Cross-Sectional Data on Wages |
| bw.subset | Cross-Sectional Data on Wages |
-- C --
| cps71 | Canadian High School Graduate Earnings |
-- D --
| dimBS | Local-Polynomial Basis Dimension Helper |
-- E --
| Engel95 | 1995 British Family Expenditure Survey |
-- F --
| fitted.npcopula | Kernel Copula Estimation with Mixed Data Types |
-- G --
| gradients | Extract Gradients |
| gradients.condensity | Extract Gradients |
| gradients.condistribution | Extract Gradients |
| gradients.npregression | Extract Gradients |
| gradients.qregression | Extract Gradients |
| gradients.singleindex | Extract Gradients |
-- I --
| Italy | Italian GDP Panel |
-- L --
| lamhosts | Hosts Information |
-- M --
| mpi.barrier | MPI_Barrier API |
| mpi.bcast | MPI_Bcast API |
| mpi.bcast.cmd | Extension of MPI_Bcast API |
| mpi.bcast.Robj | Extensions of MPI_Bcast API |
| mpi.bcast.Robj2slave | Extensions of MPI_Bcast API |
| mpi.close.Rslaves | Close and Inspect R Slaves |
| mpi.comm.dup | MPI_Comm_dup, MPI_Comm_rank, and MPI_Comm_size APIs |
| mpi.comm.free | MPI_Comm_free API |
| mpi.comm.rank | MPI_Comm_dup, MPI_Comm_rank, and MPI_Comm_size APIs |
| mpi.comm.size | MPI_Comm_dup, MPI_Comm_rank, and MPI_Comm_size APIs |
| mpi.exit | Exit MPI Environment |
| mpi.get.processor.name | MPI_Get_processor_name API |
| mpi.get.version | MPI_Get_version API |
| mpi.hostinfo | Host Information Utilities |
| mpi.is.master | Hosts Information |
| mpi.quit | Exit MPI Environment |
-- N --
| np.kernels | Kernel Functions Used In 'npRmpi' |
| np.mpi.initialize | Initialize Ranks for Manual-Broadcast npRmpi Workflows |
| np.options | Global Package Options for 'npRmpi' |
| np.pairs | Cross-Validated Pairs Plot (Helper Functions) |
| np.pairs.plot | Cross-Validated Pairs Plot (Helper Functions) |
| npcdens | Kernel Conditional Density Estimation with Mixed Data Types |
| npcdens.conbandwidth | Kernel Conditional Density Estimation with Mixed Data Types |
| npcdens.default | Kernel Conditional Density Estimation with Mixed Data Types |
| npcdens.formula | Kernel Conditional Density Estimation with Mixed Data Types |
| npcdensbw | Kernel Conditional Density Bandwidth Selection with Mixed Data Types |
| npcdensbw.conbandwidth | Kernel Conditional Density Bandwidth Selection with Mixed Data Types |
| npcdensbw.default | Kernel Conditional Density Bandwidth Selection with Mixed Data Types |
| npcdensbw.formula | Kernel Conditional Density Bandwidth Selection with Mixed Data Types |
| npcdenshat | Conditional Density Hat Operator |
| npcdist | Kernel Conditional Distribution Estimation with Mixed Data Types |
| npcdist.condbandwidth | Kernel Conditional Distribution Estimation with Mixed Data Types |
| npcdist.default | Kernel Conditional Distribution Estimation with Mixed Data Types |
| npcdist.formula | Kernel Conditional Distribution Estimation with Mixed Data Types |
| npcdistbw | Kernel Conditional Distribution Bandwidth Selection with Mixed Data Types |
| npcdistbw.condbandwidth | Kernel Conditional Distribution Bandwidth Selection with Mixed Data Types |
| npcdistbw.default | Kernel Conditional Distribution Bandwidth Selection with Mixed Data Types |
| npcdistbw.formula | Kernel Conditional Distribution Bandwidth Selection with Mixed Data Types |
| npcdisthat | Conditional Distribution Hat Operator |
| npcmstest | Kernel Consistent Model Specification Test with Mixed Data Types |
| npconmode | Kernel Modal Regression with Mixed Data Types |
| npconmode.conbandwidth | Kernel Modal Regression with Mixed Data Types |
| npconmode.default | Kernel Modal Regression with Mixed Data Types |
| npconmode.formula | Kernel Modal Regression with Mixed Data Types |
| npcopula | Kernel Copula Estimation with Mixed Data Types |
| npcopula.default | Kernel Copula Estimation with Mixed Data Types |
| npcopula.formula | Kernel Copula Estimation with Mixed Data Types |
| npdeneqtest | Kernel Consistent Density Equality Test with Mixed Data Types |
| npdeptest | Kernel Consistent Pairwise Nonlinear Dependence Test for Univariate Processes |
| npindex | Semiparametric Single Index Model |
| npindex.default | Semiparametric Single Index Model |
| npindex.formula | Semiparametric Single Index Model |
| npindex.sibandwidth | Semiparametric Single Index Model |
| npindexbw | Semiparametric Single Index Model Parameter and Bandwidth Selection |
| npindexbw.default | Semiparametric Single Index Model Parameter and Bandwidth Selection |
| npindexbw.formula | Semiparametric Single Index Model Parameter and Bandwidth Selection |
| npindexbw.sibandwidth | Semiparametric Single Index Model Parameter and Bandwidth Selection |
| npindexhat | Experimental Hat Operators for Semiparametric Estimators |
| npksum | Kernel Sums with Mixed Data Types |
| npksum.default | Kernel Sums with Mixed Data Types |
| npksum.formula | Kernel Sums with Mixed Data Types |
| npksum.numeric | Kernel Sums with Mixed Data Types |
| npplreg | Partially Linear Kernel Regression with Mixed Data Types |
| npplreg.default | Partially Linear Kernel Regression with Mixed Data Types |
| npplreg.formula | Partially Linear Kernel Regression with Mixed Data Types |
| npplreg.plbandwidth | Partially Linear Kernel Regression with Mixed Data Types |
| npplregbw | Partially Linear Kernel Regression Bandwidth Selection with Mixed Data Types |
| npplregbw.default | Partially Linear Kernel Regression Bandwidth Selection with Mixed Data Types |
| npplregbw.formula | Partially Linear Kernel Regression Bandwidth Selection with Mixed Data Types |
| npplregbw.plbandwidth | Partially Linear Kernel Regression Bandwidth Selection with Mixed Data Types |
| npplreghat | Experimental Hat Operators for Semiparametric Estimators |
| npqcmstest | Kernel Consistent Quantile Regression Model Specification Test with Mixed Data Types |
| npqreg | Kernel Quantile Regression with Mixed Data Types |
| npqreg.condbandwidth | Kernel Quantile Regression with Mixed Data Types |
| npqreg.default | Kernel Quantile Regression with Mixed Data Types |
| npqreg.formula | Kernel Quantile Regression with Mixed Data Types |
| npquantile | Kernel Univariate Quantile Estimation |
| npreg | Kernel Regression with Mixed Data Types |
| npreg.default | Kernel Regression with Mixed Data Types |
| npreg.formula | Kernel Regression with Mixed Data Types |
| npreg.rbandwidth | Kernel Regression with Mixed Data Types |
| npregbw | Kernel Regression Bandwidth Selection with Mixed Data Types |
| npregbw.default | Kernel Regression Bandwidth Selection with Mixed Data Types |
| npregbw.formula | Kernel Regression Bandwidth Selection with Mixed Data Types |
| npregbw.rbandwidth | Kernel Regression Bandwidth Selection with Mixed Data Types |
| npreghat | Nonparametric Regression Hat Operator |
| npreghat.formula | Nonparametric Regression Hat Operator |
| npreghat.npregression | Nonparametric Regression Hat Operator |
| npreghat.rbandwidth | Nonparametric Regression Hat Operator |
| npregiv | Nonparametric Instrumental Regression |
| npregivderiv | Nonparametric Instrumental Derivatives |
| npRmpi | Parallel Nonparametric Kernel Smoothing Methods for Mixed Data Types |
| npRmpi.init | Init/Quit Helpers for Session and Attach npRmpi Workflows |
| npRmpi.quit | Init/Quit Helpers for Session and Attach npRmpi Workflows |
| npRmpi.session.info | Init/Quit Helpers for Session and Attach npRmpi Workflows |
| npscoef | Smooth Coefficient Kernel Regression |
| npscoef.default | Smooth Coefficient Kernel Regression |
| npscoef.formula | Smooth Coefficient Kernel Regression |
| npscoef.scbandwidth | Smooth Coefficient Kernel Regression |
| npscoefbw | Smooth Coefficient Kernel Regression Bandwidth Selection |
| npscoefbw.default | Smooth Coefficient Kernel Regression Bandwidth Selection |
| npscoefbw.formula | Smooth Coefficient Kernel Regression Bandwidth Selection |
| npscoefbw.scbandwidth | Smooth Coefficient Kernel Regression Bandwidth Selection |
| npscoefhat | Experimental Hat Operators for Semiparametric Estimators |
| npsdeptest | Kernel Consistent Serial Dependence Test for Univariate Nonlinear Processes |
| npseed | Set Random Seed |
| npsigtest | Kernel Regression Significance Test with Mixed Data Types |
| npsigtest.default | Kernel Regression Significance Test with Mixed Data Types |
| npsigtest.formula | Kernel Regression Significance Test with Mixed Data Types |
| npsigtest.npregression | Kernel Regression Significance Test with Mixed Data Types |
| npsigtest.rbandwidth | Kernel Regression Significance Test with Mixed Data Types |
| npsymtest | Kernel Consistent Density Asymmetry Test with Mixed Data Types |
| nptgauss | Truncated Second-order Gaussian Kernels |
| npudens | Kernel Density Estimation with Mixed Data Types |
| npudens.bandwidth | Kernel Density Estimation with Mixed Data Types |
| npudens.default | Kernel Density Estimation with Mixed Data Types |
| npudens.formula | Kernel Density Estimation with Mixed Data Types |
| npudensbw | Kernel Density Bandwidth Selection with Mixed Data Types |
| npudensbw.bandwidth | Kernel Density Bandwidth Selection with Mixed Data Types |
| npudensbw.default | Kernel Density Bandwidth Selection with Mixed Data Types |
| npudensbw.formula | Kernel Density Bandwidth Selection with Mixed Data Types |
| npudenshat | Unconditional Density Hat Operator |
| npudist | Kernel Distribution Estimation with Mixed Data Types |
| npudist.dbandwidth | Kernel Distribution Estimation with Mixed Data Types |
| npudist.default | Kernel Distribution Estimation with Mixed Data Types |
| npudist.formula | Kernel Distribution Estimation with Mixed Data Types |
| npudistbw | Kernel Distribution Bandwidth Selection with Mixed Data Types |
| npudistbw.dbandwidth | Kernel Distribution Bandwidth Selection with Mixed Data Types |
| npudistbw.default | Kernel Distribution Bandwidth Selection with Mixed Data Types |
| npudistbw.formula | Kernel Distribution Bandwidth Selection with Mixed Data Types |
| npudisthat | Unconditional Distribution Hat Operator |
| npuniden.boundary | Kernel Bounded Univariate Density Estimation Via Boundary Kernel Functions |
| npuniden.reflect | Kernel Bounded Univariate Density Estimation Via Data-Reflection |
| npuniden.sc | Kernel Shape Constrained Bounded Univariate Density Estimation |
| npunitest | Kernel Consistent Univariate Density Equality Test with Mixed Data Types |
| np_boot_control | Validated plot control helpers |
| np_grid_control | Validated plot control helpers |
| np_render_control | Validated plot control helpers |
-- O --
| oecdpanel | Cross Country Growth Panel |
-- P --
| plot.bandwidth | General Purpose Plotting of Nonparametric Objects |
| plot.conbandwidth | General Purpose Plotting of Nonparametric Objects |
| plot.conmode | Kernel Modal Regression with Mixed Data Types |
| plot.np | General Purpose Plotting of Nonparametric Objects |
| plot.npcopula | Kernel Copula Estimation with Mixed Data Types |
| plot.plbandwidth | General Purpose Plotting of Nonparametric Objects |
| plot.qregression | Kernel Quantile Regression with Mixed Data Types |
| plot.rbandwidth | General Purpose Plotting of Nonparametric Objects |
| plot.scbandwidth | General Purpose Plotting of Nonparametric Objects |
| plot.sibandwidth | General Purpose Plotting of Nonparametric Objects |
| predict.conmode | Kernel Modal Regression with Mixed Data Types |
| predict.npcopula | Kernel Copula Estimation with Mixed Data Types |
| predict.npreghat | Nonparametric Regression Hat Operator |
| predict.qregression | Kernel Quantile Regression with Mixed Data Types |
| print.npcopula | Kernel Copula Estimation with Mixed Data Types |
| print.npreghat | Nonparametric Regression Hat Operator |
-- S --
| se | Extract Standard Errors |
| se.npcopula | Kernel Copula Estimation with Mixed Data Types |
| slave.hostinfo | Host Information Utilities |
| summary.npcopula | Kernel Copula Estimation with Mixed Data Types |
-- T --
| tailslave.log | Close and Inspect R Slaves |
-- U --
| uocquantile | Compute Quantiles |
-- W --
| wage1 | Cross-Sectional Data on Wages |