The package offers a fitting of smooth varying coefficients in an additiv two-way hazard model.
A one-way hazard model can also be fittied with supplementary functions. Nonparametric penalized spline (p-spline) fitting is proposed.
In the two-way case two alternativ models can be analized: In the first one a non periodic calendar time, like the calendar year, is considered
as a second time scale (additionaly to the survival time), and as a spline basis truncated polynomial functions are chosen.
In the second model a periodic time scale, like a season of year, is additionaly considered, and as a spline basis the b-splines
are selected. In the one-way case the user can choose between these two alternative penalized bases.

Systematic approaches using TW-SLM for incorporating control spots and data quality information to improve normalization of cDNA microarray data.
TwslmSpikeWeight is for normalization of cDNA microarray data with
the two-way semilinear model(TW-SLM). It incorporates information from
control spots and data quality in the TW-SLM to improve normalization of
cDNA microarray data. Huber's and Tukey's bisquare
weight functions are available for robust estimation of the TW-SLM.

Functions to Simulate and Conduct Dose-Escalation Phase I
Studies
Benjamin Esterni with contribution from Baboukar Mane
Two Phase I designs are implemented in the package: the classical 3+3 and the Continual Reassessment Method. Simulations tools are also available to estimate the operating characteristics of the methods with several user-dependent options.

UBCRM is a R package containing functions to simulate and
conduct dose escalation phase I studies.
Two designs are implemented in the package: the classical 3+3 and the Continual Reassessment Method. Simulations tools are also available to estimate the operating characteristics of the methods with several user-dependant options

An Implementation of Several Approaches to Utility-Based
Learning for Both Classification and Regression Tasks
Provides a set of functions that can be used to obtain better predictive performance on cost-sensitive and cost/benefits tasks (for both regression and classification). This includes re-sampling approaches, cost-based methods, special purpose evaluation metrics as well as specific learning systems.
c(person("Paula", "Branco", email = "paobranco@gmail.com", role = c("aut", "cre")), person("Rita", "Ribeiro", email = "rpribeiro@dcc.fc.up.pt", role = c("aut", "ctb")), person("Luis", "Torgo", email = "ltorgo@dcc.fc.up.pt", role = c("aut", "ctb")))
Paula Branco [aut, cre],
Rita Ribeiro [aut, ctb],
Luis Torgo [aut, ctb]