AdaptFitOS-package {AdaptFitOS}R Documentation

Adaptive Semiparametric Additive Regression with Simultaneous Confidence Bands and Specification Tests

Description

Based on package AdaptFit, fits semiparametric regression models with spatially adaptive penalized splines and computes simultaneous confidence bands and associated specification (lack-of-fit) tests. For computation of the critical value for simultaneous confidence bands based on Hotelling's volume-of-tube formula, some functions of the libtube library by Catherine Loader (see package locfit) are used. See the references for details on the construction of the confidence bands.

Details

The DESCRIPTION file:

Package: AdaptFitOS
Title: Adaptive Semiparametric Additive Regression with Simultaneous Confidence Bands and Specification Tests
Version: 0.67
Date: 2018-05-16
Author: Manuel Wiesenfarth and Tatyana Krivobokova
Maintainer: Manuel Wiesenfarth <m.wiesenfarth@dkfz.de>
Imports: mgcv, SemiPar
Depends: nlme, MASS, splines
Description: Fits semiparametric additive regression models with spatially adaptive penalized splines and computes simultaneous confidence bands and associated specification (lack-of-fit) tests. Simultaneous confidence bands cover the entire curve with a prescribed level of confidence and allow us to assess the estimation uncertainty for the whole curve. In contrast to pointwise confidence bands, they permit statements about the statistical significance of certain features (e.g. bumps) in the underlying curve.The method allows for handling of spatially heterogeneous functions and their derivatives as well as heteroscedasticity in the data. See Wiesenfarth et al (2012) <doi:10.1080/01621459.2012.682809>.
License: GPL (>=2)

Index of help topics:

AdaptFitOS-package      Adaptive Semiparametric Additive Regression
                        with Simultaneous Confidence Bands and
                        Specification Tests
asp2                    Fit a semiparametric regression model with
                        spatially adaptive penalized splines
aspFormula              An asp formula
aspHetero               Estimate varying residual variance
default.knots           Compute default knots for a given x vector
fitted.asp              Fitted values for semiparametric regression.
plot.asp                Plots fitted curves or their derivatives
predict.asp             Semiparametric regression prediction.
residuals.asp           Residuals for semiparametric regression.
scbM                    Calculate simultaneous confidence bands for
                        penalized splines
sigma                   Extract estimated varying residual variance
summary.asp             Summaries and hypothesis tests

Model estimation using the mixed model representation of penalized splines in combination with simultaneous probability calculations based on the volume-of-tube formula enable the simultaneous inference directly, that is, without resampling methods.

The function asp2() is used to fit the model. Using the resulting asp object, fitted curves or their derivatives can be plotted with plot.asp and information on the parametric effects as well as specification tests for the nonparametric effects can be printed using summary.asp.

See Wiesenfarth et al (2012) for technical details and Wiesenfarth (2012, Chapter 5.1) for some more details on the use of the package (including a demonstration on how plots in Wiesenfarth et al are obtained).

Author(s)

Manuel Wiesenfarth and Tatyana Krivobokova

Maintainer: Manuel Wiesenfarth <m.wiesenfarth at dkfz de>

References

Krivobokova, T., Crainiceanu, C.M. and Kauermann, G. (2008)
Fast Adaptive Penalized Splines. Journal of Computational and Graphical Statistics, 17(1):1-20.

Krivobokova, T., Kneib, T., and Claeskens, G. (2010)
Simultaneous confidence bands for penalized spline estimators. Journal of the American Statistical Association, 105(490):852-863.

Wiesenfarth, M., Krivobokova, T., Klasen, S., Sperlich, S. (2012).
Direct Simultaneous Inference in Additive Models and its Application to Model Undernutrition. Journal of the American Statistical Association, 107(500): 1286-1296.

Wiesenfarth, M. (2012). Estimation and Inference in Special Nonparametric Models. Doctoral dissertation, Goettingen, Georg-August Universitaet, Diss., 2012. http://d-nb.info/104297182X/34

See Also

spm (package SemiPar), asp (package AdaptFit)


[Package AdaptFitOS version 0.67 Index]