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scam (version 1.0)

Shape constrained additive models

Description

Routines for generalized additive modelling under shape constraints on the component functions of the linear predictor. Models can contain multiple shape constrained (univariate and/or bivariate) and unconstrained terms. The routines of mgcv(gam) package are used for setting up the model matrix, printing and plotting the results. Penalized likelihood maximization based on Newton-Raphson method to fit a model with multiple smoothing parameter selection by GCV or UBRE/AIC.

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Version

Install

install.packages('scam')

Monthly Downloads

33,760

Version

1.0

License

GPL (>= 2)

Maintainer

Natalya Pya

Last Published

January 20th, 2012

Functions in scam (1.0)

predict.scam

Prediction from fitted SCAM model
residuals.scam

SCAM residuals
marginal.matrices.tesmi1.ps

Constructs marginal model matrices for "tesmi1" and "tesmd1" bivariate smooths in case of B-splines basis functions for both unconstrained marginal smooths
marginal.matrices.tesmi2.ps

Constructs marginal model matrices for "tesmi2" and "tesmd2" bivariate smooths in case of B-splines basis functions for both unconstrained marginal smooths
monotonic.smooth.terms

Shape preserving smooth terms in SCAM
plot.scam

SCAM plotting
scam.check

Some diagnostics for a fitted scam object
scam.fit

Newton-Raphson method to fit SCAM
gcv.ubre_grad

The GCV/UBRE score value and its gradient
smooth.construct.tedmi.smooth.spec

Tensor product smoothing constructor for bivariate function subject to double monotone increasing constraint
smooth.construct.tesmd1.smooth.spec

Tensor product smoothing constructor for a bivariate function monotone decreasing in the first covariate
smooth.construct.tesmd2.smooth.spec

Tensor product smoothing constructor for a bivariate function monotone decreasing in the second covariate
summary.scam

Summary for a SCAM fit
smooth.construct.mpd.smooth.spec

Constructor for monotone decreasing P-splines in SCAMs
smooth.construct.mdcx.smooth.spec

Constructor for monotone decreasing and convex P-splines in SCAMs
derivative.smooth

Derivative of the univariate constrained smooth term
smooth.construct.tesmi2.smooth.spec

Tensor product smoothing constructor for a bivariate function monotone increasing in the second covariate
bfgs_gcv.ubre

Multiple Smoothing Parameter Estimation by GCV/UBRE
scam-package

Shape constrained additive models
smooth.construct.tedmd.smooth.spec

Tensor product smoothing constructor for bivariate function subject to double monotone decreasing constraint
scam

Shape constrained additive models (SCAM) and integrated smoothness selection
smooth.construct.mdcv.smooth.spec

Constructor for monotone decreasing and concave P-splines in SCAMs
smooth.construct.micv.smooth.spec

Constructor for monotone increasing and concave P-splines in SCAMs
smooth.construct.mpi.smooth.spec

Constructor for monotone increasing P-splines in SCAMs
check.analytical

Checking the analytical gradient of the GCV/UBRE score
print.scam

Print a SCAM object
smooth.construct.tesmi1.smooth.spec

Tensor product smoothing constructor for a bivariate function monotone increasing in the first covariate
Predict.matrix.mpi.smooth

Predict matrix method functions for SCAMs
smooth.construct.micx.smooth.spec

Constructor for monotone increasing and convex P-splines in SCAMs