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assist (version 3.1.8)

A Suite of R Functions Implementing Spline Smoothing Techniques

Description

Fit various smoothing spline models. Includes an ssr() function for smoothing spline regression, an nnr() function for nonparametric nonlinear regression, an snr() function for semiparametric nonlinear regression, an slm() function for semiparametric linear mixed-effects models, and an snm() function for semiparametric nonlinear mixed-effects models. See Wang (2011) for an overview.

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Version

Install

install.packages('assist')

Monthly Downloads

411

Version

3.1.8

License

GPL-2

Maintainer

Yuedong Wang

Last Published

August 12th, 2022

Functions in assist (3.1.8)

Calculate reproducing kernels for Stein shrinkage estimate

Treasury and GE bonds

Interface to Fortran Subroutine dsms

Bayesian Confidence Interval Plot of a Smoothing Spline Fit

Calculate Reproducing Kernels for Periodic Polynomial Splines with Period 1

Interface of dbmdr, dbimdr, dgmdr, dpmdr in GRKPACK.

Monthly Mean Temperatures

Calculate Reproducing Kernels for Periodic L-Splines with Period 1/2

Coronary Ainus Potassium Concentrations

Construct a Block Diagonal Matrix

A Modified Cholesky Decomposition

Testing a Non-parametric Function Fitted via Smoothing Splines

Chickenpox in New York City

Hormone Measurements of Cortisol

Calculate the Inverse Logit Transformation

Texas Historical Climate Data

Calculate Predictions and Posterior Standard Deviations of Spline Estimates From a slm Object

Fit a Semi-parametric Linear Mixed Effects Model

Interface of dmudr subroutine in RKPACK

Scaling a Vector

Fit a Monotone Curve Using a Cubic Spline

Calculate Reproducing Kernels for Thin Plate Splines

Monthly Mean Ozone Thickness in Arosa of Switzerland

Interface of dsidr subroutines in RKPACK

Predictions from a Semiparametric Nonlinear Mixed Effects Model Fit

Calculate Predictions and Approximate Posterior Standard Deviations for Spline Estimates From a snr Object

Predict Method from a Semiparametric Nonlinear Regression Model Fit

Calculate Reproducing Kernels for Polynomial Splines on [0, 1]

Calculate reproducing kernels for one-dimensional space

Calculate product of reproducing kernels

print.summary.slm

Calculate Predictions and Approximate Posterior Standard Deviations for Spline Estimates From a nnr Object

print.summary.snm

Interface of dbsdr, dbisdr, dgsdr, dpsdr in GRKPACK.

Extension of XYPLOT

Fit a General Smoothing Spline Regression Model

Calculate Pseudo Reproducing Kernels for Spherical Splines

Generate Diagnostic Plots for a ssr Object

Predict Method for Semiparametric Linear Mixed Effects Model Fits

print.summary.snr

Calculate Predictions and Approximate Posterior Standard Deviations for Spline Estimate From a snm Object

Winter Average Temperatures

Extract the Hat Matrix from a ssr Object

Interface to Fortran Subroutine dcrdr

print.summary.ssr

Calculate Reproducing Kernels for Some L-splines

Calculate Predictions and Posterior Standard Deviations for a ssr Object

Fit A Semi-parametric Nonlinear Regression Model

print.anova.ssr

Print an anova.ssr Object

Set Control Parameters for nnr

Growth of paramecium caudatum population

Set Control Parameters for snr

Fit a Semi-parametric Nonlinear Mixed-effects Model

Nonlinear Non-parametric Regression

print.summary.nnr

Set Control Parameters for snm

Set Control Parameters for `ssr'

A fitted ssr Object

Object Summaries

Object Summaries

IEEG segments from a seizure patient

Summarize a ssr object

Wisconsin Epidemiological Study of Diabetic Retinopathy

Average Winter temperature in the United States

Ultrasound imaging of the tongue shape

Object Summaries

Magnitude of the Mira Variable R Hydrae

Daily maximum temperatures in Stratford

Object Summaries

Calculate Reproducing Kernels for Polynomial Splines on [0, T]

Lake Acidity Study