bigsplines: Smoothing Splines for Large Samples
Version 1.1-0

Fits smoothing spline regression models using scalable algorithms designed for large samples. Seven marginal spline types are supported: linear, cubic, different cubic, cubic periodic, cubic thin-plate, ordinal, and nominal. Random effects and parametric effects are also supported. Response can be Gaussian or non-Gaussian: Binomial, Poisson, Gamma, Inverse Gaussian, or Negative Binomial.

Browse man pages Browse package API and functions Browse package files

AuthorNathaniel E. Helwig <helwig@umn.edu>
Date of publication2017-02-03 14:32:57
MaintainerNathaniel E. Helwig <helwig@umn.edu>
LicenseGPL (>= 2)
Version1.1-0
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("bigsplines")

Man pages

bigspline: Fits Smoothing Spline
bigsplines-internal: Internal functions for big splines package
bigsplines-package: Smoothing Splines for Large Samples
bigssa: Fits Smoothing Spline ANOVA Models
bigssg: Fits Generalized Smoothing Spline ANOVA Models
bigssp: Fits Smoothing Splines with Parametric Effects
bigtps: Fits Cubic Thin-Plate Splines
binsamp: Bin-Samples Strategic Knot Indices
imagebar: Displays a Color Image with Colorbar
makessa: Makes Objects to Fit Smoothing Spline ANOVA Models
makessg: Makes Objects to Fit Generalized Smoothing Spline ANOVA...
makessp: Makes Objects to Fit Smoothing Splines with Parametric...
ordspline: Fits Ordinal Smoothing Spline
plotbar: Generic X-Y Plotting with Colorbar
plotci: Generic X-Y Plotting with Confidence Intervals
predict.bigspline: Predicts for "bigspline" Objects
predict.bigssa: Predicts for "bigssa" Objects
predict.bigssg: Predicts for "bigssg" Objects
predict.bigssp: Predicts for "bigssp" Objects
predict.bigtps: Predicts for "bigtps" Objects
predict.ordspline: Predicts for "ordspline" Objects
print: Prints Fit Information for bigsplines Model
ssBasis: Smoothing Spline Basis for Polynomial Splines
summary: Summarizes Fit Information for bigsplines Model

Functions

MPinv Man page Source code
bigspline Man page Source code
bigsplines Man page
bigsplines-package Man page
bigssa Man page Source code
bigssg Man page Source code
bigssp Man page Source code
bigtps Man page Source code
binsamp Man page Source code
gcvcss Man page Source code
gcvgss Man page Source code
gcvoss Man page Source code
gcvssa Man page Source code
gcvssg Man page Source code
gcvssp Man page Source code
getRandom Man page Source code
imagebar Man page Source code
lamcoef Man page Source code
lamcoefg Man page Source code
lamloop Man page Source code
lamloopg Man page Source code
makeZtX Man page Source code
makeZtZ Man page Source code
makerkm Man page Source code
makessa Man page Source code
makessg Man page Source code
makessp Man page Source code
nbmle Man page Source code
num2col Man page Source code
ordspline Man page Source code
pdsXty Man page Source code
pinvsm Man page Source code
plotbar Man page Source code
plotci Man page Source code
postvar Man page Source code
predict.bigspline Man page Source code
predict.bigssa Man page Source code
predict.bigssg Man page Source code
predict.bigssp Man page Source code
predict.bigtps Man page Source code
predict.ordspline Man page Source code
print.bigspline Man page Source code
print.bigssa Man page Source code
print.bigssg Man page Source code
print.bigssp Man page Source code
print.bigtps Man page Source code
print.ordspline Man page Source code
print.summary.bigspline Man page Source code
print.summary.bigssa Man page Source code
print.summary.bigssg Man page Source code
print.summary.bigssp Man page Source code
print.summary.bigtps Man page Source code
remlri Man page Source code
remlvc Man page Source code
rkron Man page Source code
smartssa Man page Source code
smartssg Man page Source code
smartssp Man page Source code
ssBasis Man page Source code
ssadpm Man page Source code
ssawork Man page Source code
ssblup Man page Source code
ssgwork Man page Source code
sspdpm Man page Source code
sspwork Man page Source code
summary.bigspline Man page Source code
summary.bigssa Man page Source code
summary.bigssg Man page Source code
summary.bigssp Man page Source code
summary.bigtps Man page Source code
tcprod Man page Source code
unifqsum Man page Source code
unifqsumg Man page Source code

Files

src
src/linker.f
src/cubkerzsym.f
src/sumfreq.f
src/nomker.f
src/perker.f
src/ordker.f
src/cubkersym.f
src/linkersym.f
src/nomkersym.f
src/perkersym.f
src/tpsker.f
src/ordkermon.f
src/ordkersym.f
src/cubker.f
src/tpskersym.f
src/cubkerz.f
NAMESPACE
R
R/postvar.R
R/predict.bigssg.R
R/remlri.R
R/gcvcss.R
R/bigssp.R
R/tcprod.R
R/lamcoefg.R
R/predict.bigtps.R
R/makessg.R
R/imagebar.R
R/bigssg.R
R/rkron.R
R/nbmle.R
R/print.bigssg.R
R/getRandom.R
R/plotci.R
R/print.summary.bigssp.R
R/remlvc.R
R/print.bigssp.R
R/summary.bigssp.R
R/smartssg.R
R/lamcoef.R
R/ssgwork.R
R/gcvssa.R
R/print.summary.bigssg.R
R/predict.bigssa.R
R/sspwork.R
R/print.summary.bigtps.R
R/bigtps.R
R/makessa.R
R/smartssa.R
R/summary.bigssg.R
R/ordspline.R
R/summary.bigtps.R
R/print.bigssa.R
R/bigspline.R
R/makeZtZ.R
R/predict.bigspline.R
R/print.ordspline.R
R/lamloop.R
R/sspdpm.R
R/binsamp.R
R/print.bigtps.R
R/ssBasis.R
R/makerkm.R
R/bigssa.R
R/pdsXty.R
R/num2col.R
R/print.summary.bigssa.R
R/plotbar.R
R/smartssp.R
R/ssblup.R
R/MPinv.R
R/gcvssp.R
R/ssadpm.R
R/makeZtX.R
R/unifqsum.R
R/summary.bigspline.R
R/gcvssg.R
R/unifqsumg.R
R/gcvoss.R
R/gcvgss.R
R/summary.bigssa.R
R/pinvsm.R
R/ssawork.R
R/predict.bigssp.R
R/print.summary.bigspline.R
R/print.bigspline.R
R/makessp.R
R/predict.ordspline.R
R/lamloopg.R
MD5
DESCRIPTION
ChangeLog
man
man/plotbar.Rd
man/bigsplines-internal.Rd
man/ssBasis.Rd
man/bigspline.Rd
man/predict.bigssp.Rd
man/makessp.Rd
man/predict.bigspline.Rd
man/imagebar.Rd
man/predict.ordspline.Rd
man/bigssa.Rd
man/makessg.Rd
man/bigssg.Rd
man/bigssp.Rd
man/ordspline.Rd
man/plotci.Rd
man/predict.bigtps.Rd
man/print.Rd
man/predict.bigssg.Rd
man/binsamp.Rd
man/bigtps.Rd
man/makessa.Rd
man/predict.bigssa.Rd
man/summary.Rd
man/bigsplines-package.Rd
bigsplines documentation built on May 19, 2017, noon