runit.NA.R
In timeSeries: Financial Time Series Objects (Rmetrics)

# Rmetrics is free software; you can redistribute it and/or
# modify it under the terms of the GNU Library General Public
# License as published by the Free Software Foundation; either
# version 2 of the License, or (at your option) any later version.
#
# Rmetrics is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Library General Public License for more details.
#
# You should have received a copy of the GNU Library General
# Public License along with this library; if not, write to the
# Free Foundation, Inc., 59 Temple Place, Suite 330, Boston,
# MA  02111-1307  USA


################################################################################


## test.removeNA =
## function()
## {
## 
##     # Create matrix object:
##     set.seed(1985)
##     M = 5
##     N = 20
##     x = matrix(round(rnorm(M*N), 3), ncol = M)
##     colnames(x) = 1:M
##     rownames(x) = 1:N
##     nNA = 10
##     nCol = trunc(runif(nNA, 1, M+1))
##     nRow = trunc(runif(nNA, 1, N+1))
##     for (i in 1:nNA) x[nRow[i], nCol[i]] = NA
##     print(x)
##     ans = removeNA(x)
##     print(ans)
## 
##     # Create data.frame object:
##     x.df = as.data.frame(x)
##     class(x.df)
##     ans = removeNA(x.df)
##     print(ans)
##     class(ans)
## 
##     # Create timeSeries object:
##     tD = timeCalendar(m = 1, d = 1:N)
##     x.tS = timeSeries(x, tD)
##     print(x.tS)
##     ans = removeNA(x.tS)
##     print(ans)
##     class(ans)
## 
##     # Return Value:
##     return()
## }
## 
## 
## # ------------------------------------------------------------------------------
## 
## 
## test.substituteNA =
## function()
## {
##     # Create matrix object:
##     set.seed(1985)
##     M = 5
##     N = 20
##     x = matrix(round(rnorm(M*N), 3), ncol = M)
##     colnames(x) = 1:M
##     rownames(x) = 1:N
##     nNA = 10
##     nCol = trunc(runif(nNA, 1, M+1))
##     nRow = trunc(runif(nNA, 1, N+1))
##     for (i in 1:nNA) x[nRow[i], nCol[i]] = NA
##     print(x)
## 
##     # Substitute:
##     ans = substituteNA(x)
##     print(ans)
##     ans = substituteNA(x, "mean")
##     print(ans)
##     ans = substituteNA(x, "median")
##     print(ans)
## 
##     # Create data.frame object:
##     x.df = as.data.frame(x)
##     print(x.df)
##     class(x.df)
## 
##     # Substitute:
##     ans = substituteNA(x.df)
##     print(ans)
##     ans = substituteNA(x.df, "mean")
##     print(ans)
##     ans = substituteNA(x.df, "median")
##     print(ans)
## 
##     # Create timeSeries object:
##     tD = timeCalendar(m = 1, d = 1:N)
##     x.tS = timeSeries(x, tD)
##     print(x.tS)
##     class(x.tS)
## 
##     # Substitute:
##     ans = substituteNA(x.tS)
##     print(ans)
##     ans = substituteNA(x.tS, "mean")
##     print(ans)
##     ans = substituteNA(x.tS, "median")
##     print(ans)
## 
##     # Return Value:
##     return()
## }


# ------------------------------------------------------------------------------


## test.interpNA =
## function()
## {
##     # Interpolate Column-by-Column
## 
##     # Create matrix object:
##     set.seed(1985)
##     M = 5
##     N = 20
##     x = matrix(round(rnorm(M*N), 3), ncol = M)
##     colnames(x) = 1:M
##     rownames(x) = 1:N
##     nNA = 10
##     nCol = trunc(runif(nNA, 1, M+1))
##     nRow = trunc(runif(nNA, 1, N+1))
##     for (i in 1:nNA) x[nRow[i], nCol[i]] = NA
##     print(x)
## 
##     # Interpolate:
##     ans = interpNA(x, "linear")
##     print(ans)
##     ans = interpNA(x, "before")
##     print(ans)
##     ans = interpNA(x, "after")
##     print(ans)
## 
##     # Return Value:
##     return()
## }


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