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scam (version 1.2-18)

Shape Constrained Additive Models

Description

Generalized additive models under shape constraints on the component functions of the linear predictor. Models can include multiple shape-constrained (univariate and bivariate) and unconstrained terms. Routines of the package 'mgcv' are used to set up the model matrix, print, and plot the results. Multiple smoothing parameter estimation by the Generalized Cross Validation or similar. See Pya and Wood (2015) for an overview. A broad selection of shape-constrained smoothers, linear functionals of smooths with shape constraints, and Gaussian models with AR1 residuals.

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Version

Install

install.packages('scam')

Monthly Downloads

8,118

Version

1.2-18

License

GPL (>= 2)

Maintainer

Natalya Pya

Last Published

January 17th, 2025

Functions in scam (1.2-18)

Predict.matrix.mpi.smooth

Predict matrix method functions for SCAMs
anova.scam

Approximate hypothesis tests related to SCAM fits
print.scam

Print a SCAM object
scam.check

Some diagnostics for a fitted scam object
qq.scam

QQ plots for scam model residuals
formula.scam

SCAM formula
scam

Shape constrained additive models (SCAM) and integrated smoothness selection
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
residuals.scam

SCAM residuals
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
smooth.construct.cx.smooth.spec

Constructor for convex P-splines in SCAMs
predict.scam

Prediction from fitted SCAM model
plot.scam

SCAM plotting
smooth.construct.lmpi.smooth.spec

Locally shape-constrained P-spline based constructor (LSCOP-spline): locally increasing splines up to a change point.
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
smooth.construct.mdcv.smooth.spec

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

Constructor for monotone increasing P-splines in SCAMs
smooth.construct.po.smooth.spec

Constructor for SCOP-splines with positivity constraint
shape.constrained.smooth.terms

Shape preserving smooth terms in SCAM
scam-package

tools:::Rd_package_title("scam")
smooth.construct.tescv.smooth.spec

Tensor product smoothing constructor for a bivariate function concave in the second covariate
smooth.construct.tescx.smooth.spec

Tensor product smoothing constructor for a bivariate function convex in the second covariate
smooth.construct.cv.smooth.spec

Constructor for concave P-splines in SCAMs
smooth.construct.temicv.smooth.spec

Tensor product smoothing constructor for bivariate function subject to mixed constraints: monotone increasing constraint wrt the first covariate and concavity wrt the second one
smooth.construct.micv.smooth.spec

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

Tensor product smoothing constructor for bivariate function subject to mixed constraints: monotone increasing constraint wrt the first covariate and convexity wrt the second one
smooth.construct.micx.smooth.spec

Constructor for monotone increasing and convex P-splines in SCAMs
smooth.construct.tecvcv.smooth.spec

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

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

Constructor for monotone increasing SCOP-splines with an additional 'finish at zero' constraint
smooth.construct.tesmd2.smooth.spec

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

Tensor product smoothing constructor for bivariate function subject to mixed constraints: convexity constraint wrt the first covariate and concavity wrt the second one
smooth.construct.tecxcx.smooth.spec

Tensor product smoothing constructor for bivariate function subject to double convexity constraint
smooth.construct.miso.smooth.spec

Constructor for monotone increasing SCOP-splines with an additional 'start at zero' constraint
summary.scam

Summary for a SCAM fit
vis.scam

Visualization of SCAM objects
scam.fit

Newton-Raphson method to fit SCAM
smooth.construct.tedmd.smooth.spec

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

Setting SCAM fitting defaults
smooth.construct.tedecv.smooth.spec

Tensor product smoothing constructor for bivariate function subject to mixed constraints: monotone decreasing constraint wrt the first covariate and concavity wrt the second one
smooth.construct.tedecx.smooth.spec

Tensor product smoothing constructor for bivariate function subject to mixed constraints: monotone decreasing constraint wrt the first covariate and convexity wrt the second one
smooth.construct.tesmi1.smooth.spec

Tensor product smoothing constructor for a bivariate function monotone increasing in the first covariate
smooth.construct.tesmi2.smooth.spec

Tensor product smoothing constructor for a bivariate function monotone increasing in the second covariate
smooth.construct.tismd.smooth.spec

Tensor product interaction with decreasing constraint along the first covariate and unconstrained along the second covariate
smooth.construct.tismi.smooth.spec

Tensor product interaction with increasing constraint along the first covariate and unconstrained along the second covariate
smooth.construct.tedmi.smooth.spec

Tensor product smoothing constructor for bivariate function subject to double monotone increasing constraint
gcv.ubre_grad

The GCV/UBRE score value and its gradient
marginal.matrices.tescv.ps

Constructs marginal model matrices for "tescv" and "tescx" bivariate smooths in case of B-splines basis functions for both unconstrained marginal smooths
bfgs_gcv.ubre

Multiple Smoothing Parameter Estimation by GCV/UBRE
logLik.scam

Log likelihood for a fitted SCAM, for AIC
derivative.scam

Derivative of the univariate smooth model terms
check.analytical

Checking the analytical gradient of the GCV/UBRE score
linear.functional.terms

Linear functionals of a smooth in GAMs