TRES (version 1.1.1)

EEG: Electroencephalography (EEG) dataset for alcoholism study.

Description

EEG images data of subjects in alcoholic and control groups.

Usage

data("EEG")

Format

A list consisting of three components:

x

A \(1 \times 84\) matrix, denoting the subject in alcoholic and control groups as 1 and 0 respectively.

y

A \(64 \times 64 \times 84\) tensor, consisting 84 channels by time EEG images.

References

URL: https://archive.ics.uci.edu/ml/datasets/EEG+Database.

Li L, Zhang X (2017). <U+201C>Parsimonious Tensor Response Regression.<U+201D> Journal of the American Statistical Association, 112(519), 1131<U+2013>1146.

Examples

# NOT RUN {
data("EEG")
x <- EEG$x; y <- EEG$y
## Estimate the envelope dimension, which turns out to be c(1,1).
# u <- TensEnv_dim(x, y)
u <- c(1,1)

## Fit the dataset with TRR.fit
fit_1D <- TRR.fit(x, y, u, method = "1D")

## The coefficient plot and p-value plot
plot(fit_1D, xlab = "Time", ylab = "Channels", yticks = seq(64,0, length.out=5))

## Uncomment to display the plots from different methods.
# fit_ols <- TRR.fit(x, y, method = "standard")
# fit_pls <- TRR.fit(x, y, u, method = "PLS")
# plot(fit_ols, xlab = "Time", ylab = "Channels", yticks = seq(64,0, length.out=5))
# plot(fit_pls, xlab = "Time", ylab = "Channels", yticks = seq(64,0, length.out=5))

# }