Package: bigsplines 1.1-1

Nathaniel E. Helwig

bigsplines: Smoothing Splines for Large Samples

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.

Authors:Nathaniel E. Helwig <[email protected]>

bigsplines_1.1-1.tar.gz
bigsplines_1.1-1.tar.gz(r-4.5-noble)bigsplines_1.1-1.tar.gz(r-4.4-noble)
bigsplines_1.1-1.tgz(r-4.4-emscripten)bigsplines_1.1-1.tgz(r-4.3-emscripten)
bigsplines.pdf |bigsplines.html
bigsplines/json (API)

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

Peer review:

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

87 exports 0.61 score 1 dependencies 2 dependents 488 downloads

Last updated 6 years agofrom:9ddb95e9af

Exports:bigsplinebigssabigssgbigsspbigtpsbinsampcubkercubkersymcubkerzcubkerzsymgcvcssgcvgssgcvossgcvssagcvssggcvsspgetRandomimagebarlamcoeflamcoefglamlooplamloopglinkerlinkersymmakerkmmakessamakessgmakesspmakeZtXmakeZtZMPinvnbmlenomkernomkersymnum2colordkerordkermonordkersymordsplinepdsXtyperkerperkersympinvsmplotbarplotcipostvarpredict.bigsplinepredict.bigssapredict.bigssgpredict.bigssppredict.bigtpspredict.ordsplineprint.bigsplineprint.bigssaprint.bigssgprint.bigsspprint.bigtpsprint.ordsplineprint.summary.bigsplineprint.summary.bigssaprint.summary.bigssgprint.summary.bigsspprint.summary.bigtpsremlriremlvcrkronsmartssasmartssgsmartsspssadpmssaworkssBasisssblupssgworksspdpmsspworksumfreqsummary.bigsplinesummary.bigssasummary.bigssgsummary.bigsspsummary.bigtpstcprodtpskertpskersymunifqsumunifqsumg

Dependencies:quadprog