Package: scam 1.2-22

Natalya Pya

scam: Shape Constrained Additive Models

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) <doi:10.1007/s11222-013-9448-7> for an overview. A broad selection of shape-constrained smoothers, linear functionals of smooths with shape constraints, and Gaussian models with AR1 residuals.

Authors:Natalya Pya [aut, cre]

scam_1.2-22.tar.gz
scam_1.2-22.tar.gz(r-4.7-arm64)scam_1.2-22.tar.gz(r-4.7-x86_64)scam_1.2-22.tar.gz(r-4.6-arm64)scam_1.2-22.tar.gz(r-4.6-x86_64)
scam_1.2-22.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
scam/json (API)

# Install 'scam' in R:
install.packages('scam', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

7.71 score 5 stars 37 packages 420 scripts 11k downloads 5 mentions 106 exports 4 dependencies

Last updated from:0e43f56b59. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK195
linux-devel-x86_64OK168
source / vignettesOK174
linux-release-arm64OK160
linux-release-x86_64OK167
wasm-releaseOK95

Exports:anova.scambfgs_gcv.ubrecheck.analyticalderivative.scamformula.scamgcv.ubre_gradlogLik.scammarginal.matrices.tescv.psmarginal.matrices.tesmi1.psmarginal.matrices.tesmi2.psplot.scamPredict.matrix.cpopspline.smoothPredict.matrix.cv.smoothPredict.matrix.cvBy.smoothPredict.matrix.cx.smoothPredict.matrix.cxBy.smoothPredict.matrix.dpo.smoothPredict.matrix.ipo.smoothPredict.matrix.lipl.smoothPredict.matrix.lmpi.smoothPredict.matrix.mdcv.smoothPredict.matrix.mdcvBy.smoothPredict.matrix.mdcx.smoothPredict.matrix.mdcxBy.smoothPredict.matrix.micv.smoothPredict.matrix.micvBy.smoothPredict.matrix.micx.smoothPredict.matrix.micxBy.smoothPredict.matrix.mifo.smoothPredict.matrix.miso.smoothPredict.matrix.mpd.smoothPredict.matrix.mpdBy.smoothPredict.matrix.mpi.smoothPredict.matrix.mpiBy.smoothPredict.matrix.po.smoothPredict.matrix.tecvcv.smoothPredict.matrix.tecxcv.smoothPredict.matrix.tecxcx.smoothPredict.matrix.tedecv.smoothPredict.matrix.tedecx.smoothPredict.matrix.tedmd.smoothPredict.matrix.tedmi.smoothPredict.matrix.temicv.smoothPredict.matrix.temicx.smoothPredict.matrix.tescv.smoothPredict.matrix.tescx.smoothPredict.matrix.tesmd1.smoothPredict.matrix.tesmd2.smoothPredict.matrix.tesmi1.smoothPredict.matrix.tesmi2.smoothPredict.matrix.tismd.smoothPredict.matrix.tismi.smoothpredict.scamprint.anova.scamprint.scamprint.summary.scamqq.scamresiduals.scamscamscam.checkscam.controlscam.fitsmooth.construct.cpop.smooth.specsmooth.construct.cv.smooth.specsmooth.construct.cvBy.smooth.specsmooth.construct.cx.smooth.specsmooth.construct.cxBy.smooth.specsmooth.construct.dpo.smooth.specsmooth.construct.ipo.smooth.specsmooth.construct.lipl.smooth.specsmooth.construct.lmpi.smooth.specsmooth.construct.mdcv.smooth.specsmooth.construct.mdcvBy.smooth.specsmooth.construct.mdcx.smooth.specsmooth.construct.mdcxBy.smooth.specsmooth.construct.micv.smooth.specsmooth.construct.micvBy.smooth.specsmooth.construct.micx.smooth.specsmooth.construct.micxBy.smooth.specsmooth.construct.mifo.smooth.specsmooth.construct.miso.smooth.specsmooth.construct.mpd.smooth.specsmooth.construct.mpdBy.smooth.specsmooth.construct.mpi.smooth.specsmooth.construct.mpiBy.smooth.specsmooth.construct.po.smooth.specsmooth.construct.tecvcv.smooth.specsmooth.construct.tecxcv.smooth.specsmooth.construct.tecxcx.smooth.specsmooth.construct.tedecv.smooth.specsmooth.construct.tedecx.smooth.specsmooth.construct.tedmd.smooth.specsmooth.construct.tedmi.smooth.specsmooth.construct.temicv.smooth.specsmooth.construct.temicx.smooth.specsmooth.construct.tescv.smooth.specsmooth.construct.tescx.smooth.specsmooth.construct.tesmd1.smooth.specsmooth.construct.tesmd2.smooth.specsmooth.construct.tesmi1.smooth.specsmooth.construct.tesmi2.smooth.specsmooth.construct.tismd.smooth.specsmooth.construct.tismi.smooth.specsummary.scamvcov.scamvis.scam

Dependencies:latticeMatrixmgcvnlme

Readme and manuals

Help Manual

Help pageTopics
Shape Constrained Additive Modelsscam-package
Approximate hypothesis tests related to SCAM fitsanova.scam print.anova.scam
Derivative of the univariate smooth model termsderivative.scam
Linear functionals of a smooth in GAMsfunction.predictors linear.functional.terms signal.regression
Log likelihood for a fitted SCAM, for AICAIC.scam logLik.scam
SCAM plottingplot.scam
Prediction from fitted SCAM modelpredict.scam
Print a SCAM objectprint.scam
QQ plots for scam model residualsqq.scam
SCAM residualsresiduals.scam
Shape constrained additive models (SCAM) and integrated smoothness selectionscam
Some diagnostics for a fitted scam objectscam.check
Setting SCAM fitting defaultsscam.control
Shape preserving smooth terms in SCAMshape.constrained.smooth.terms
Constructor for concave P-splines in SCAMssmooth.construct.cv.smooth.spec smooth.construct.cvBy.smooth.spec
Constructor for convex P-splines in SCAMssmooth.construct.cx.smooth.spec smooth.construct.cxBy.smooth.spec
Locally shape-constrained P-spline based constructor (LSCOP-spline): locally increasing splines up to a change point.smooth.construct.lipl.smooth.spec smooth.construct.lmpi.smooth.spec
Constructor for monotone decreasing and concave P-splines in SCAMssmooth.construct.mdcv.smooth.spec smooth.construct.mdcvBy.smooth.spec
Constructor for monotone decreasing and convex P-splines in SCAMssmooth.construct.mdcx.smooth.spec smooth.construct.mdcxBy.smooth.spec
Constructor for monotone increasing and concave P-splines in SCAMssmooth.construct.micv.smooth.spec smooth.construct.micvBy.smooth.spec
Constructor for monotone increasing and convex P-splines in SCAMssmooth.construct.micx.smooth.spec smooth.construct.micxBy.smooth.spec
Constructor for monotone increasing SCOP-splines with an additional 'finish at zero' constraintsmooth.construct.mifo.smooth.spec
Constructor for monotone increasing SCOP-splines with an additional 'start at zero' constraintsmooth.construct.miso.smooth.spec
Constructor for monotone decreasing P-splines in SCAMssmooth.construct.mpd.smooth.spec smooth.construct.mpdBy.smooth.spec
Constructor for monotone increasing P-splines in SCAMssmooth.construct.mpi.smooth.spec smooth.construct.mpiBy.smooth.spec
Constructor for SCOP-splines with positivity constraintsmooth.construct.cpop.smooth.spec smooth.construct.dpo.smooth.spec smooth.construct.ipo.smooth.spec smooth.construct.po.smooth.spec
Tensor product smoothing constructor for bivariate function subject to double concavity constraintsmooth.construct.tecvcv.smooth.spec
Tensor product smoothing constructor for bivariate function subject to mixed constraints: convexity constraint wrt the first covariate and concavity wrt the second onesmooth.construct.tecxcv.smooth.spec
Tensor product smoothing constructor for bivariate function subject to double convexity constraintsmooth.construct.tecxcx.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 onesmooth.construct.tedecv.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 onesmooth.construct.tedecx.smooth.spec
Tensor product smoothing constructor for bivariate function subject to double monotone decreasing constraintsmooth.construct.tedmd.smooth.spec
Tensor product smoothing constructor for bivariate function subject to double monotone increasing constraintsmooth.construct.tedmi.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 onesmooth.construct.temicv.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 onesmooth.construct.temicx.smooth.spec
Tensor product smoothing constructor for a bivariate function concave in the second covariatesmooth.construct.tescv.smooth.spec
Tensor product smoothing constructor for a bivariate function convex in the second covariatesmooth.construct.tescx.smooth.spec
Tensor product smoothing constructor for a bivariate function monotone decreasing in the first covariatesmooth.construct.tesmd1.smooth.spec
Tensor product smoothing constructor for a bivariate function monotone decreasing in the second covariatesmooth.construct.tesmd2.smooth.spec
Tensor product smoothing constructor for a bivariate function monotone increasing in the first covariatesmooth.construct.tesmi1.smooth.spec
Tensor product smoothing constructor for a bivariate function monotone increasing in the second covariatesmooth.construct.tesmi2.smooth.spec
Tensor product interaction with decreasing constraint along the first covariate and unconstrained along the second covariatesmooth.construct.tismd.smooth.spec
Tensor product interaction with increasing constraint along the first covariate and unconstrained along the second covariatesmooth.construct.tismi.smooth.spec
Summary for a SCAM fitprint.summary.scam summary.scam
Parameter estimator covariance matrix from SCAM fitvcov.scam
Visualization of SCAM objectspersp vis.scam