\name{TV}
\Rdversion{1.1}
\alias{TV}

\title{TV Viewing Data}

\description{This data set \code{TV} comprises a 5 x 11 x 3 contingency table based on
  audience viewing data from Neilsen Media Research for the week starting
  November 6, 1995.
}

\usage{data(TV)}
\format{
  A 5 x 11 x 3 array of cell frequencies with the following structure:
\preformatted{
 int [1:5, 1:11, 1:3] 146 244 233 174 294 151 181 161 183 281 ...
 - attr(*, "dimnames")=List of 3
  ..$ Day    : chr [1:5] "Monday" "Tuesday" "Wednesday" "Thursday" ...
  ..$ Time   : chr [1:11] "8:00" "8:15" "8:30" "8:45" ...
  ..$ Network: chr [1:3] "ABC" "CBS" "NBC"
}
}

\details{
The original data, \code{tv.dat}, contains two additional networks: "Fox" and "Other", with small
frequencies. These levels were removed in the current version.
There is also a fourth factor, transition State
transition (turn the television Off, Switch channels, or Persist in viewing the current channel).
The \code{TV} data here includes only the Persist observations.
}

\source{
The original data, \code{tv.dat}, came from the initial implementation of 
mosaic displays in R by Jay Emerson (1998). Similar data had been used by
Hartigan and Kleiner (1984) as an illustration.
}

\references{
Friendly, M. and Meyer, D. (2016). 
\emph{Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data}. 
Boca Raton, FL: Chapman & Hall/CRC. \url{http://ddar.datavis.ca}.

Emerson, John W. Mosaic Displays in S-PLUS: A General Implementation and a Case Study.
\emph{Statistical Graphics and Computing Newsletter}, 1998, 9(1), 17--23, 
\url{http://www.stat.yale.edu/~jay/R/mosaic/v91.pdf}

Hartigan, J. A. & Kleiner, B. A Mosaic of Television Ratings. \emph{The American Statistician}, 1984, 38, 32-35.
  
  
}

\examples{
data(TV)
structable(TV)
doubledecker(TV)

# reduce number of levels of Time
TV.df <- as.data.frame.table(TV)
levels(TV.df$Time) <- rep(c("8:00-8:59", "9:00-9:59", "10:00-10:44"), 
                          c(4, 4, 3))

TV2 <- xtabs(Freq ~ Day + Time + Network, TV.df)

# re-label for mosaic display
levels(TV.df$Time) <- c("8", "9", "10")
# fit mode of joint independence, showing association of Network with Day*Time
mosaic(~ Day + Network + Time, 
  data = TV.df, 
  expected = ~ Day:Time + Network, 
  legend = FALSE)


# with doubledecker arrangement
mosaic(~ Day + Network + Time, 
  data = TV.df, 
  expected = ~ Day:Time + Network,
  split = c(TRUE, TRUE, FALSE), 
  spacing = spacing_highlighting, 
  legend = FALSE)
}

\keyword{datasets}
