Displays the same concise one-line summary statistics report as
gx.summary1 for two or more columns of a matrix or data frame. The table consists of a heading line and a line of summary statistics for each ‘variable’, column of the matrix or data frame. Optionally the data may be logarithmically (base 10) transformed.
name of the matrix or data frame.
the indices, or names (see Example), of the columns of the matrix or data frame for the variables whose summary statistics are to be displayed.
by default the character string for
if the summary statistics are required following a log10 transformation, set
log = TRUE results in a log transformation for the parametric statistical estimates. The maximum, minimum, quartiles and robust estimates of spread are estimated and reported in natural measurement units. Of the parametric statistics, the mean (the geometric mean) and 95%confidence are reported backtransformed into natural measurement units.
Any less than detection limit values represented by negative values, or zeros or other numeric codes representing blanks in the data, must be removed prior to executing this function, see
NAs in the data vector will be removed prior to computation in function
gx.stats. Display of the number of
NAs found by function
remove.na is suppressed in
remove.na as the information is included in the display from this function.
For a more extensive summary statistics display a variable at a time, see
gx.summary2, and for a summary with graphical displays see
For summary graphical presentations see functions
Robert G. Garrett
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## Make test data available data(kola.o) attach(kola.o) ## Generates an initial display for As , Co , Cu , ## Ni  and Zn  gx.summary.mat(kola.o, c(6, 13, 15, 24, 38)) ## Alternately gx.summary.mat(kola.o, c("As", "Co", "Cu", "Ni", "Zn")) ## Provide a more informative display for Be , La , P , ## Th , U  and Y gx.summary.mat(kola.o, c(9, 19, 25, 33, 35, 37), banner = "Kola Project, <2 mm O-horizon soils") ## As above but with a log10 transformation to display ## the geometric mean, etc. gx.summary.mat(kola.o, c("Be", "La", "P", "Th", "U", "Y"), log = TRUE, banner = "Kola Project, <2 mm O-horizon soils") ## Detach test data detach(kola.o)