This package provides statistical inference tools applied to Partial Linear Regression (PLR) models. Specifically, point estimation, confidence intervals estimation, bandwidth selection, goodness-of-fit tests and analysis of covariance are considered. Kernel-based methods, combined with ordinary least squares estimation, are used and time series errors are allowed. In addition, these techniques are also implemented for both parametric (linear) and nonparametric regression models.

Author | German Aneiros Perez and Ana Lopez Cheda |

Date of publication | 2014-01-01 21:37:58 |

Maintainer | German Aneiros Perez <ganeiros@udc.es> |

License | GPL |

Version | 1.1 |

**best.arima:** Best Arima model according some information criterion

**Epanechnikov:** The Epanechnikov kernel

**gaussian:** The gaussian kernel

**np.ancova:** Nonparametric analysis of covariance

**np.cv:** Cross-validation bandwidth selection in nonparametric...

**np.est:** Nonparametric estimate of the regression function

**np.gcv:** Generalized cross-validation bandwidth selection in...

**np.gof:** Goodness-of-Fit tests in nonparametric regression models

**par.ancova:** Parametric analysis of covariance (based on linear models)

**par.ci:** Confidence intervals estimation in linear regression models

**par.est:** Estimation in linear regression models

**par.gof:** Goodness-of-Fit tests in linear regression models

**plrm.ancova:** Semiparametric analysis of covariance (based on PLR models)

**plrm.beta:** Semiparametric estimate for the parametric component of the...

**plrm.ci:** Confidence intervals estimation in partial linear regression...

**plrm.cv:** Cross-validation bandwidth selection in PLR models

**plrm.est:** Semiparametric estimates for the unknown components of the...

**plrm.gcv:** Generalized cross-validation bandwidth selection in PLR...

**plrm.gof:** Goodness-of-Fit tests in PLR models

**PLRModels:** Statistical inference in partial linear regression models

**quadratic:** The quadratic kernel

**symsolve:** Solution of a system of linear equations

**triweight:** The triweight kernel

**uniform:** The uniform kernel

**var.cov.matrix:** Estimated variance-covariance matrix from time series

**var.cov.sum:** Estimated sum of autocovariances from time series

PLRModels

PLRModels/NAMESPACE

PLRModels/data

PLRModels/data/barnacles2.txt.gz

PLRModels/data/barnacles1.txt.gz

PLRModels/R

PLRModels/R/par.ancova.R
PLRModels/R/plrm.gcv.R
PLRModels/R/np.est.R
PLRModels/R/par.gof.R
PLRModels/R/var.cov.sum.R
PLRModels/R/plrm.cv.R
PLRModels/R/var.cov.matrix.R
PLRModels/R/plrm.ancova.R
PLRModels/R/plrm.beta.R
PLRModels/R/par.ci.R
PLRModels/R/np.cv.R
PLRModels/R/best.arima.R
PLRModels/R/plrm.est.R
PLRModels/R/np.gof.R
PLRModels/R/np.gcv.R
PLRModels/R/kind.of.kernel.R
PLRModels/R/symsolve.R
PLRModels/R/plrm.ci.R
PLRModels/R/par.est.R
PLRModels/R/plrm.gof.R
PLRModels/R/np.ancova.R
PLRModels/MD5

PLRModels/DESCRIPTION

PLRModels/man

PLRModels/man/np.cv.Rd
PLRModels/man/np.gof.Rd
PLRModels/man/plrm.gcv.Rd
PLRModels/man/quadratic.Rd
PLRModels/man/par.ancova.Rd
PLRModels/man/barnacles1.rd

PLRModels/man/plrm.cv.Rd
PLRModels/man/gaussian.Rd
PLRModels/man/triweight.Rd
PLRModels/man/barnacles2.rd

PLRModels/man/best.arima.Rd
PLRModels/man/plrm.ci.Rd
PLRModels/man/plrm.est.Rd
PLRModels/man/np.gcv.Rd
PLRModels/man/plrm.beta.Rd
PLRModels/man/var.cov.matrix.Rd
PLRModels/man/PLRModels.Rd
PLRModels/man/plrm.ancova.Rd
PLRModels/man/uniform.Rd
PLRModels/man/par.gof.Rd
PLRModels/man/var.cov.sum.Rd
PLRModels/man/Epanechnikov.Rd
PLRModels/man/np.ancova.Rd
PLRModels/man/par.est.Rd
PLRModels/man/np.est.Rd
PLRModels/man/symsolve.Rd
PLRModels/man/plrm.gof.Rd
PLRModels/man/par.ci.Rd
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