Data Smoothing by Interpolating Cubic Splines
c(
person("Juraj", "Hudak", role = c("aut")),
person("Viliam", "Kacala", email = "viliam.kacala.ml@gmail.com", role = c("cre")),
person("Csaba", "Torok", email = "csaba.torok@upjs.sk", role = c("ctb")))
We construct the explicit form of clamped cubic interpolating spline (both uniform - knots are equidistant and non-uniform - knots are arbitrary). Using this form, we propose a linear regression model suitable for real data smoothing. This package is based on a diploma thesis Hudak (2017) <https://opac.crzp.sk/?fn=detailBiblioForm&sid=7FE4E0810F66E41DF9A9CA23557F&seo=CRZP-detail-kniha>.
Juraj Hudak [aut],
Viliam Kacala [cre],
Csaba Torok [ctb]

Juraj Hudak, Lubomir Antoni, Csaba Torok
We construct the explicit form of clamped cubic interpolating spline (both uniform - knots are equidistant and non-uniform - knots are arbitrary). Using this form, we propose a linear regression model suitable for real data smoothing.

Indirect Cross-Validation (ICV) for Kernel Density Estimation
Functions for computing the global and local Gaussian density estimates based on the ICV bandwidth. See the article of Savchuk, O.Y., Hart, J.D., Sheather, S.J. (2010). Indirect cross-validation for density estimation. Journal of the American Statistical Association, 105(489), 415-423 <doi:10.1198/jasa.2010.tm08532>.

Cox Model with Interval-Censored Starting Time of a Covariate
Calibration and risk-set calibration methods for fitting Cox proportional hazard model when a binary covariate is measured intermittently. Methods include functions to fit calibration models from interval-censored data and modified partial likelihood for the proportional hazard model, Nevo et al. (2018+) <arXiv:1801.01529>.
Rcpp (>= 0.12.5), survival, fitdistrplus, icenReg, numDeriv,
ICsurv, msm, MASS

An Ensemble Method for Interval-Censored Survival Data
c(person(given = "Weichi", family = "Yao", role = c("aut", "cre"),
email = "wy635@stern.nyu.edu"),
person(given = "Halina", family = "Frydman", role = "aut", email = "hf2@stern.nyu.edu"),
person(given = "Jeffrey S.", family = "Simonoff", role = "aut", email = "jss2@stern.nyu.edu"))
Weichi Yao [aut, cre],
Halina Frydman [aut],
Jeffrey S. Simonoff [aut]
stats, utils, graphics, survival, icenReg, ipred, parallel
Implements the conditional inference forest approach
to modeling interval-censored survival data. It also provides
functions to tune the parameters and evaluate the model fit. See
Yao et al. (2019) <arXiv:1901.04599>.