Packaged: Thu Sep  6 16:02:03 2007; lena

Description: Fits a non-linear transformation model (nltm) for
analyzing survival data, see Tsodikov (2003)
approach". J.R. Statistical Society B, 65, Part 3, 759-774. The
class of nltm includes the following currently supported
models: Cox proportional hazard, proportional hazard cure,
proportional odds, proportional hazard - proportional hazard
cure, proportional hazard - proportional odds cure, Gamma
frailty, and proportional hazard - proportional odds.

Author: Gilda Garibotti, Alexander Tsodikov, Mark Clements
Description: Fits a non-linear transformation model ('nltm') for
analyzing survival data, see Tsodikov (2003) <doi:10.1111/1467-9868.00414>. The
class of 'nltm' includes the following currently supported

Packaged: Wed Feb 11 09:57:23 2009; lena

Description: R functions for (non)linear time series analysis. A core
topic is order estimation through cross-validation.
Depends: R (>= 2.2.0), locfit (>= 1.5.3), acepack, akima
X-CRAN-Comment: Earlier versions of this packae have been removed as
they contained material not licensed under 'GPL'.

Depends: R (>= 2.2.0), locfit (>= 1.5.3), acepack

Description: R functions for (non)linear time series analysis with an emphasis on nonparametric autoregression and order estimation, and tests for linearity / additivity.

Title: Network Meta-Analysis using Integrated Nested Laplace
person("Burak Kuersad", "Guenhan", email = "burak.gunhan@med.uni-goettingen.de", role = c("aut", "cre")))
Description: Performs network meta-analysis using integrated nested Laplace approximations ('INLA'). Includes methods to assess the heterogeneity and inconsistency in the network. Contains more than ten different network meta-analysis data. Installation of R package 'INLA' is compulsory for successful usage. 'INLA' package can be obtained from <http://www.r-inla.org>. We recommend the testing version.

Description: Performs network meta-analysis using integrated nested Laplace approximations ('INLA'). Includes methods to assess the heterogeneity and inconsistency in the network. Contains more than ten different network meta-analysis data. 'INLA' package can be obtained from <http://www.r-inla.org>. We recommend the testing version.