Description Usage Arguments Details Value Side effects Note Author(s) References See Also Examples
Read data from fn.txt (space delimited text file) or fn.csv
(comma delimited text file) and calculate all summary statistics using
IH.summary
. Output results to an ASCII text file fnout.csv in CSV format
1 |
fn |
name of input data file in double quotes without the .txt or .csv extension |
L |
L is specified limit for the exceedance fraction; e.g., the occupational exposure limit |
bcol |
Column that contains the BY variable–see details. Default NA |
rto |
Round values to rto. Default = 5 |
pstat |
Select a subset of statistics calculated by |
reverse |
If |
p |
probability for Xp the 100pth percentile. Default is 0.95 |
gam |
one-sided confidence level γ. Default is 0.95 |
comma |
if |
Read data from a tab or comma delimited text file in the
current folder/directory. The first column must contain measurements
(observed X values). The second column is an indicator variable with 1 for a
detected value and 0 for a non-detect. Additional columns can contain
factors that can be used to define a BY variable. The first record
in the file must contain valid R names. Valid names may contain
letters (case sensitive), numbers, period, and underscore and should
start with a letter ( no spaces). This file would most likely be
obtained from an Excel spread sheet using the file "Save As" option,
with file Save as type:
Text(Tab delimited)(*.txt) or CSV(Comma
delimited)(*.csv).
Returns invisible data.frame from file fn.txt
Column 1 |
value of measurement |
Column 2 |
indicator variable ; 1 for detect 0 for non-detect |
Column 3 |
… additional variables |
Summary statistics calculated by
IH.summary
are computed for each subset of data as
defined by the levels of the BY variable. A data frame with row names
from IH.summary (or subset based on value of pstat
) and column
names defined by the values of the BY variable is output as an ASCII
text file in CSV format fnout.csv in the working folder. If
reverse
is TRUE the rows and columns are reversed.
For information about factor
see R help file factor
Each level of the BY variable must have at least two non-detects for this function.
If this is not the case an error message is printed to the R console and the
levels of the BY variable with less than 3 non-detects are printed.
E. L. Frome
see the help file for lnorm.ml
, efclnp
efraction.ml
, percentile.ml
, kmms
About-STAND
for more details and a complete reference list
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | # to demonstrate the use of readss add a new factor grp to the cansdata
# this factor with four levels (A_1 A_2 B_1 B_2) combines strata and sample
data(cansdata)
grp <- paste(cansdata$strata,cansdata$sample,sep="_")
temp <- data.frame(cansdata,grp) # add four level factor grp to cansdata
# the next line is NOT executable use CUT AND PASTE
# sink("demoread.txt") ; print(temp) ; sink()
# The preceding line writes temp to a text file demoread.txt in the current folder
# This file would normally be created by another program, e.g. Excel
# now use readss() to read this space delimited text file and calculate
# all of the summary statistics for each level of grp and output
# the results to a new text file demoreadout.csv in the current folder
# rdemo <- readss("demoread",L=0.2,bcol=5)
# rdemo is the R data frame that was used to calculate results in demoreadout.csv
# to see same results rounded to three places in R console use
# round( IH.summary(rdemo,L=0.2,bcol=5), 3)
# To select a subset of statistics from IH.summary first define the subset
# psel<-c("Xp.obs","Xp","Xp.UCL","f","f.UCL","Rsq","m","n")
# entering the following command will overwrite demoreadout.csv
# with rows and columns reversed and the subset of statistics as columns
# and the results will be rounded to 4 places
# rdemo <- readss("demoread",L=0.2,bcol=5,rto=4,pstat=psel,rev=TRUE)
#
# to see same results rounded to three places in R console use
# t(round( IH.summary(rdemo,L=0.2,bcol=5)[psel,], 3))
|
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