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Simulated dataset

Source: R/datasets.R
sim_data.Rd

This dataset provides explantory variables simulations and censoring status.

Format

A data frame with 1000 observations on the following 11 variables.

status

a binary vector

X1

a numeric vector

X2

a numeric vector

X3

a numeric vector

X4

a numeric vector

X5

a numeric vector

X6

a numeric vector

X7

a numeric vector

X8

a numeric vector

X9

a numeric vector

X10

a numeric vector

References

Maumy, M., Bertrand, F. (2023). PLS models and their extension for big data. Joint Statistical Meetings (JSM 2023), Toronto, ON, Canada.

Maumy, M., Bertrand, F. (2023). bigPLS: Fitting and cross-validating PLS-based Cox models to censored big data. BioC2023 — The Bioconductor Annual Conference, Dana-Farber Cancer Institute, Boston, MA, USA. Poster. https://doi.org/10.7490/f1000research.1119546.1

Bastien, P., Bertrand, F., Meyer, N., and Maumy-Bertrand, M. (2015). Deviance residuals-based sparse PLS and sparse kernel PLS for binary classification and survival analysis. BMC Bioinformatics, 16, 211.

Examples


# \donttest{
data(sim_data)
X_sim_data_train <- sim_data[1:800,2:11]
C_sim_data_train <- sim_data$status[1:800]
X_sim_data_test <- sim_data[801:1000,2:11]
C_sim_data_test <- sim_data$status[801:1000]
rm(X_sim_data_train,C_sim_data_train,X_sim_data_test,C_sim_data_test)
# }