Hi Atem,
May be this works.
### Q1: working directory: Observed #Only one file per Site. Assuming this is
the
### case for the full dataset, then I guess there is no need to average
dir.create("final")
lst1 <- split(list.files(pattern = ".csv"), gsub("\\_.*", "",
list.files(pattern = ".csv")))
lst2 <- lapply(lst1, function(x1) lapply(x1, function(x2) {
lines1 <- readLines(x2)
header1 <- lines1[1:2]
dat1 <- read.table(text = lines1, header = FALSE, sep = ",",
stringsAsFactors = FALSE,
skip = 2)
colnames(dat1) <- Reduce(paste, strsplit(header1, ","))
dat1[-c(nrow(dat1), nrow(dat1) - 1), ]
}))
lst3 <- lst2[sapply(seq_along(lst2),function(i){lstN <-
sapply(lst2[[i]],function(x) is.integer(ncol(x)))})]
length(lst2)
#[1] 120
length(lst3)
#[1] 119
library(plyr)
library(stringr)
lst4 <- setNames(lapply(seq_along(lst3), function(i) {
lapply(lst3[[i]], function(x) {
names(x)[-1] <- paste(names(x)[-1], names(lst1)[i], sep = "_")
names(x) <- str_trim(names(x))
x
})[[1]]
}), names(lst3))
df1 <- join_all(lst4, by = "Year")
dim(df1)
# [1] 9 27311
dimCol <- sapply(split(names(df1)[-1], gsub(".*\\_", "", names(df1)[-1])),
function(x) {
df2 <- df1[, x]
df3 <- data.frame(Percentiles = paste0(seq(0, 100, by = 1), "%"),
numcolwise(function(y) quantile(y,
seq(0, 1, by = 0.01), na.rm = TRUE))(df2), stringsAsFactors = FALSE)
ncol(df3)
})
lst5 <- split(names(df1)[-1], gsub(".*\\_", "", names(df1)[-1]))
lapply(seq_along(lst5), function(i) {
df2 <- df1[, lst5[[i]]]
df3 <- data.frame(Percentiles = paste0(seq(0, 100, by = 1), "%"),
numcolwise(function(y) quantile(y,
seq(0, 1, by = 0.01), na.rm = TRUE))(df2), stringsAsFactors = FALSE)
write.csv(df3, paste0(paste(getwd(), "final", paste(names(lst4)[[i]],
"Quantile",
sep = "_"), sep = "/"), ".csv"), row.names = FALSE, quote = FALSE)
})
ReadOut1 <- lapply(list.files(recursive = TRUE)[grep("Quantile",
list.files(recursive = TRUE))],
function(x) read.csv(x, header = TRUE, stringsAsFactors = FALSE))
dir.create("Indices")
sapply(ReadOut1, dim)[,1:3] ##different dimensions
# [,1] [,2] [,3]
#[1,] 101 101 101
#[2,] 157 258 258
names1 <- unlist(lapply(ReadOut1, function(x) names(x)[-1]))
names2 <- gsub("\\_.*", "", names1)
names3 <- unique(gsub("[.]", " ", names2))
length(names3)
#[1] 264
#lstNew <- simplify2array(ReadOut1) ###results you got
# nrow(lstNew)
#NULL####
ReadOut2 <- lapply(seq_along(ReadOut1),function(i) {df2 <- ReadOut1[[i]]; df3
<-as.data.frame(matrix(NA,nrow=101,ncol=length(names3), dimnames=list(NULL,
names3))); names(df2) <- gsub("[.]"," ", gsub("\\_.*","", names(df2))); df2 <-
df2[,-1]; df3[,match(names(df2), names(df3))] <- df2; df3})
lstNew <- simplify2array(ReadOut2)
nrow(lstNew)
#[1] 264
lapply(1:nrow(lstNew), function(i) { dat1 <- data.frame(Percentiles =
paste0(seq(0, 100, by = 1), "%"), do.call(cbind, lstNew[i, ]), stringsAsFactors
= FALSE); colnames(dat1) <- c("Percentiles", paste(names(lst3),
rep(rownames(lstNew)[i],length(lst3)),sep="_"));
write.csv(dat1,paste0(paste(getwd(), "Indices", gsub(" ",
"_",rownames(lstNew)[i]), sep="/"),".csv"),row.names=FALSE, quote=FALSE)})
## Output2:
ReadOut2 <- lapply(list.files(recursive = TRUE)[grep("Indices",
list.files(recursive = TRUE))],
function(x) read.csv(x, header = TRUE, stringsAsFactors = FALSE))
length(ReadOut2)
#[1] 264
ReadOut2[[1]][1:3,1:3]
# Percentiles G100_pav.ANN G101_pav.ANN
#1 0% 0.766900 0.96240
#2 1% 0.796132 0.96572
#3 2% 0.825364 0.96904
Attached is the file.
A.K.
On Tuesday, April 15, 2014 4:00 AM, Zilefac Elvis <[email protected]>
wrote:
Hi AK,
I tried all codes for observations. All others work great except this (probably
due to different dimensions.
What I did is that I took the Observed.zip file, deleted the station which had
no data and applied the code. However, this section of the code did not work.
The problem is that lstNew is NULL. So, nothing is actually written to
"Indices".
I will check ReadOut1 when I get up from sleep.
Thanks,
Atem.
dir.create("Indices")
names1 <- lapply(ReadOut1, function(x) names(x))[[1]]
lstNew <- simplify2array(ReadOut1)
nrow(lstNew)
#[1] NULL
lapply(2:nrow(lstNew), function(i) { dat1 <- data.frame(lstNew[1],
do.call(cbind, lstNew[i, ]), stringsAsFactors = FALSE) colnames(dat1) <-
c(rownames(lstNew)[1], paste(names(lst1), rep(rownames(lstNew)[i],
length(lst1)), sep = "_")) write.csv(dat1, paste0(paste(getwd(), "Indices",
rownames(lstNew)[i], sep = "/"), ".csv"), row.names = FALSE, quote = FALSE)
})
===================================================================================================================
On Tuesday, April 15, 2014 12:45 AM, arun <[email protected]> wrote:
HI Atem,
No problem. Hope it works for Observation files too. Remember that before you
run the same code for sample in Observation, check the dimensions of the files
(as I did previously). If there is change of dimensions, make them the same
dimensions using the methods I showed. Then, I guess it should work.
A.K.
On Tuesday, April 15, 2014 2:21 AM, Zilefac Elvis <[email protected]>
wrote:
Hi AK,
All codes for simulation files work great.
I will try the code for observations and let you know.
Thanks very much.
Atem.
On Tuesday, April 15, 2014 12:01 AM, arun <[email protected]> wrote:
Yes,
my new solution ignores such cases.
On Monday, April 14, 2014 11:58 PM, Zilefac Elvis <[email protected]>
wrote:
Hi AK,
Please ignore any such site.
I will check it and include in the analysis.
Thanks,
Atem.
On Monday, April 14, 2014 9:34 PM, arun <[email protected]> wrote:
Hi,
I looked at your Observed.zip. In that one of the file is without any data:
GG83_Sim.csv.ind.csv
The contents of the file are just:
Year
Year
trend
p <
A.K.
On Monday, April 14, 2014 10:41 PM, Zilefac Elvis <[email protected]>
wrote:
Hi AK,
Q1) Please try to correct the error using the larger data set (Sample.zip). The
issue is that once you write the codes and restrict it to smaller data sets, I
find it difficult to generalize it to larger data sets.
Q2) From the Quantilecode2.txt you just sent, you forgot to do the following
section using the Observed.zip file. I tried to run the code to section Q1 in
Quantilecode2.txt using a larger data set and received the same error :Error in
2:nrow(lstNew) : argument of length 0. I have attached a larger data set too
for you to generalize the code to suit the larger data set. Please do not
forget to include the code below in the final code of Q2.
Once you fix these two, I should be able to fix the rest following these
examples.
Thanks AK. Sorry for overloading you with much work.
Atem.
#==============================================================================================================
dir.create("Indices")
names1 <- lapply(ReadOut1, function(x) names(x))[[1]]
lstNew <- simplify2array(ReadOut1) lapply(2:nrow(lstNew), function(i) { dat1 <-
data.frame(lstNew[1], do.call(cbind, lstNew[i, ]), stringsAsFactors = FALSE)
colnames(dat1) <- c(rownames(lstNew)[1], paste(names(lst1),
rep(rownames(lstNew)[i], length(lst1)), sep = "_"))
write.csv(dat1, paste0(paste(getwd(), "Indices", rownames(lstNew)[i], sep =
"/"), ".csv"), row.names = FALSE, quote = FALSE)
})
## Output2:
ReadOut2 <- lapply(list.files(recursive = TRUE)[grep("Indices",
list.files(recursive = TRUE))], function(x) read.csv(x, header = TRUE,
stringsAsFactors = FALSE))
length(ReadOut2)
# [1] 257
head(ReadOut2[[1]], 2)
#==============================================================================================================
On Monday, April 14, 2014 8:07 PM, arun <[email protected]> wrote:
HI,
Please send your emails in plain text. If you had looked at the dimensions of
`lst2`:
sapply(lst2,function(x) sapply(x,ncol))[1:6,]
G100 G101 G102 G103 G104 G105 G106 G107 G108 G109 G110 G111 G112 G113 G114
[1,] 258 258 258 258 258 257 258 258 258 258 258 258 258 258 247
[2,] 258 258 258 258 258 258 258 258 258 258 258 258 258 258 258
[3,] 258 258 258 258 258 258 258 258 258 258 258 258 258 258 257
[4,] 258 258 258 258 258 257 258 258 258 258 258 258 258 258 258
[5,] 258 258 258 258 258 258 258 258 258 258 258 258 258 258 258
[6,] 258 258 258 258 258 258 258 258 258 258 258 258 258 258 258
G115 G116 G117 G118 G119 G120 GG10 GG11 GG12 GG13 GG14 GG15 GG16 GG17 GG18
[1,] 258 247 256 256 258 258 258 258 258 258 258 258 258 257 258
[2,] 258 250 257 258 258 256 258 258 258 258 258 258 258 258 258
[3,] 258 247 256 258 258 256 258 258 258 258 258 258 258 258 256
[4,] 258 258 258 257 258 258 258 258 258 258 258 258 258 257 258
[5,] 258 257 258 258 258 256 258 258 258 258 258 258 258 258 258
[6,] 258 257 249 257 258 258 258 258 258 258 258 258 258 258 258
GG19 GG20 GG21 GG22 GG23 GG24 GG25 GG26 GG27 GG28
[1,] 258 258 258 258 258 258 258 258 258 258
[2,] 258 258 258 258 258 258 258 258 258 258
[3,] 258 258 257 258 256 257 258 258 258 258
[4,] 258 257 258 258 258 257 258 258 258 258
[5,] 258 258 257 258 257 258 258 258 258 258
[6,] 258 258 258 258 257 258 258 258 258 258
#the dimensions are not consistent for the Simulations
within each Site. My codes assumed that all the datasets were having the same
number of columns, rows etc.
On Monday, April 14, 2014 6:26 PM, Zilefac Elvis <[email protected]> wrote:
Hi AK,
I have another request for help.
Attached is a larger file (~27MB) for sample.zip. All files are same as
previous except that I am using more sites to do the same thing that you did
with sample.zip.
When generalizing Quantilecode.R to many sites, I receive an error when I run:
dir.create("Indices")
names1 <- lapply(ReadOut1, function(x) names(x))[[1]]
lstNew <- simplify2array(ReadOut1)
lapply(2:nrow(lstNew), function(i) {
dat1 <- data.frame(lstNew[1], do.call(cbind, lstNew[i, ]), stringsAsFactors =
FALSE)
colnames(dat1) <- c(rownames(lstNew)[1], paste(names(lst1),
rep(rownames(lstNew)[i],
length(lst1)), sep = "_"))
write.csv(dat1, paste0(paste(getwd(), "Indices", rownames(lstNew)[i], sep =
"/"),
".csv"), row.names = FALSE, quote = FALSE)
})
and I get this:
Error in 2:nrow(lstNew) : argument of length 0
I have tried a few tricks but could not overcome the error message.
Please help!
Atem.
sample (1).zip
Zilefac Elvis shared from Dropbox
View on www.dropbox.com Preview by Yahoo
On Monday, April 14, 2014 9:22 AM, arun <[email protected]> wrote:
Ok
. I got the results but mynet is down. Will send once it gets fixed
----------
Sent from my Nokia
------Original message------
From: [email protected] <[email protected]>
To: "arun" <[email protected]>
Date: Monday, April 14, 2014 3:01:38 PM GMT
Subject: Re: Re: Quantile and rowMean from multiple files in a folder
In the Observed.zip I
have just one file per site while in sample.zip I have 100 files(Sims) per site.
Thanks,
Atem.
------ Original Message ------
From : arun
To : Zilefac Elvis;
Sent : 14-04-2014 00:12
Subject : Re: Quantile and rowMean from multiple files in a folder
One more doubt, do you have more than one files per Site? In the example, it
was just one file per Site. On Monday, April 14, 2014 2:08 AM, arun
wrote: Hi, The problem is in the different dimensions of the Observed datasets.
sapply(seq_along(lst2),function(i){lstN<- lapply(lst2[[i]],function(x)
x[,-1]);sapply(lstN,function(x) nrow(x))}) ##after removing the trend and P
value rows #[1] 9 9 9 8 2 9 If you want to take the average, is it through
filling NAs for those years that are missing in the files?? A.K. On
Monday, April 14, 2014 1:05 AM, Zilefac Elvis
wrote: Hi AK, Q1) Please apply the Quantilecode.R to Observed.zip (attached).
I tried but received an error which was self-explanatory but I could not change
the dimensions in the code. Q2) Please apply Quantilecode.R to both
sample.zip and observed.zip. Here, instead of doing quantile(y, seq(0, 1, by =
0.01), take colMeans of the indices. I have tried to solve both Q1 and Q2
but still unable to control the dimensions. Thanks, Atem. On Sunday, April 13,
2014 9:05 AM, arun wrote: Hi Atem, On my end, the codes are not formatted
in the email as seen in the screen of formatR GUI. I am attaching the .R file
in case there is some difficulty for you. Arun On Sunday, April 13, 2014
10:54 AM, arun wrote: Hi, I am formatting the codes using library(formatR).
Hopefully, it will not be mangled in the email. dir.create("final") lst1<-
split(list.files(pattern
=".csv"), gsub("\\_.*","", list.files(pattern =".csv"))) lst2<- lapply(lst1,
function(x1) lapply(x1, function(x2) { lines1<- readLines(x2) header1<-
lines1[1:2] dat1<- read.table(text = lines1, header = FALSE, sep =",",
stringsAsFactors = FALSE, skip = 2) colnames(dat1)<- Reduce(paste,
strsplit(header1,",")) dat1[-c(nrow(dat1), nrow(dat1) - 1), ] }))
library(plyr) lapply(seq_along(lst2), function(i) { lstN<- lapply(lst2[[i]],
function(x) x[, -1]) lstQ1<- lapply(lstN, function(x) numcolwise(function(y)
quantile(y, seq(0, 1, by = 0.01), na.rm = TRUE))(x)) arr1<-
array(unlist(lstQ1), dim = c(dim(lstQ1[[1]]), length(lstQ1)), dimnames =
list(NULL, lapply(lstQ1, names)[[1]])) res<- rowMeans(arr1, dims = 2, na.rm =
TRUE) colnames(res)<- gsub("","_", colnames(res)) res1<- data.frame(Percentiles
= paste0(seq(0, 100, by = 1),"%"), res, stringsAsFactors = FALSE)
write.csv(res1,
paste0(paste(getwd(),"final", paste(names(lst1)[[i]],"Quantile", sep ="_"), sep
="/"),".csv"), row.names = FALSE, quote = FALSE) }) ReadOut1<-
lapply(list.files(recursive = TRUE)[grep("Quantile", list.files(recursive =
TRUE))], function(x) read.csv(x, header = TRUE, stringsAsFactors = FALSE))
sapply(ReadOut1, dim) # [,1] [,2] #[1,] 101 101 #[2,] 258 258
lapply(ReadOut1,function(x) x[1:2,1:3]) #[[1]] # Percentiles txav_DJF txav_MAM
#1 0% -12.68566 7.09702 #2 1% -12.59062 7.15338 # #[[2]] #
Percentiles txav_DJF txav_MAM #1 0% -12.75516 6.841840 #2 1%
-12.68244 6.910664 ###Q2: dir.create("Indices") names1<- lapply(ReadOut1,
function(x) names(x))[[1]] lstNew<- simplify2array(ReadOut1)
lapply(2:nrow(lstNew),
function(i) { dat1<- data.frame(lstNew[1], do.call(cbind, lstNew[i, ]),
stringsAsFactors = FALSE) colnames(dat1)<- c(rownames(lstNew)[1],
paste(names(lst1), rep(rownames(lstNew)[i], length(lst1)), sep ="_"))
write.csv(dat1, paste0(paste(getwd(),"Indices", rownames(lstNew)[i], sep ="/"),
".csv"), row.names = FALSE, quote = FALSE) }) ## Output2: ReadOut2<-
lapply(list.files(recursive = TRUE)[grep("Indices", list.files(recursive =
TRUE))], function(x) read.csv(x, header = TRUE, stringsAsFactors = FALSE))
length(ReadOut2) # [1] 257 head(ReadOut2[[1]], 2) # Percentiles G100_pav_ANN
G101_pav_ANN #1 0% 1.054380 1.032740 #2 1% 1.069457
1.045689 A.K. On Sunday, April 13, 2014 2:46 AM, Zilefac Elvis
wrote: Hi AK, Q1) I need your help again. Using the
previous data (attached) and the previous code below,instead of taking
rowMeans, let's do quantile(x,seq(0,1,by=0.01)). Delete the last 2 rows
(Trend and p<) in each file before doing quantile(x,seq(0,1,by=0.01)). For
example, assume that I want to calculate quantile(x,seq(0,1,by=0.01)) for each
column of Site G100. I will do so for the 5 sims of site G100 and then take
their average. This will be approximately close to the true value than just
calculating quantile(x,seq(0,1,by=0.01)) from one sim. Please dothis same thing
for all the files. So, when you do rowMeans, it should be the mean of
quantile(x,seq(0,1,by=0.01)) calculated from all sims in that Site. Output
The number of files in"final" remains the same (2 files). The"Year" column(will
be replaced) will contain the names of quantile(x,seq(0,1,by=0.01)) such as 0%
1% 2%
3% 4% 5% 6%, ..., 98% 99% 100% .
You can give this column any name such as"Percentiles". Q2) From the
folder"final", please go to each file identified by site name, take a column,
say col1 of txav from each file, create a dataframe whose colnames are site
codes (names of files in"final"). Create a folder called"Indices" and place
this dataframe in it. The filename for the dataframe is txav, say. So,
in"Indices", you will have one file having 3 columns [, c(Percentiles,
G100,G101)]. The idea is that I want to be able to pick any column from files
in"final" and form a dataframe from which I will generate my qqplot or boxplot.
Thanks very much AK. Atem This should be the final step of this my drama, at
least for now.
#==============================================================================================================
dir.create("final") lst1<-
split(list.files(pattern=".csv"),gsub("\\_.*","",list.files(pattern=".csv")))
lst2<- lapply(lst1,function(x1) lapply(x1, function(x2) {lines1<-
readLines(x2); header1<- lines1[1:2]; dat1<-
read.table(text=lines1,header=FALSE,sep=",",stringsAsFactors=FALSE, skip=2);
colnames(dat1)<- Reduce(paste,strsplit(header1,","));dat1})) lstYear<-
lapply(lst2,function(x) lapply(x, function(y) y[,1,drop=FALSE])[[1]])
lapply(seq_along(lst2),function(i) {lstN<-lapply(lst2[[i]],function(x) x[,-1]);
arr1<-
array(unlist(lstN),dim=c(dim(lstN[[1]]),length(lstN)),dimnames=list(NULL,lapply(lstN,names)[[1]]));res<-
cbind(lstYear[[i]],rowMeans(arr1,dims=2,na.rm=TRUE)); names(res)<-
gsub("\\_$","",gsub("","_",names(res))); res[,1]<- gsub("<","",res[,1]);
write.csv(res,paste0(paste(getwd(),"final",names(lst1)
[[i]],sep="/"),".csv"),row.names=FALSE,quote=FALSE) })
#====================================================================================================
### Q1: working directory: Observed #Only one file per Site. Assuming this is
the
### case for the full dataset, then I guess there is no need to average
dir.create("final")
lst1 <- split(list.files(pattern = ".csv"), gsub("\\_.*", "",
list.files(pattern = ".csv")))
lst2 <- lapply(lst1, function(x1) lapply(x1, function(x2) {
lines1 <- readLines(x2)
header1 <- lines1[1:2]
dat1 <- read.table(text = lines1, header = FALSE, sep = ",",
stringsAsFactors = FALSE,
skip = 2)
colnames(dat1) <- Reduce(paste, strsplit(header1, ","))
dat1[-c(nrow(dat1), nrow(dat1) - 1), ]
}))
lst3 <- lst2[sapply(seq_along(lst2),function(i){lstN <-
sapply(lst2[[i]],function(x) is.integer(ncol(x)))})]
length(lst2)
#[1] 120
length(lst3)
#[1] 119
library(plyr)
library(stringr)
lst4 <- setNames(lapply(seq_along(lst3), function(i) {
lapply(lst3[[i]], function(x) {
names(x)[-1] <- paste(names(x)[-1], names(lst1)[i], sep = "_")
names(x) <- str_trim(names(x))
x
})[[1]]
}), names(lst3))
df1 <- join_all(lst4, by = "Year")
dim(df1)
# [1] 9 27311
dimCol <- sapply(split(names(df1)[-1], gsub(".*\\_", "", names(df1)[-1])),
function(x) {
df2 <- df1[, x]
df3 <- data.frame(Percentiles = paste0(seq(0, 100, by = 1), "%"),
numcolwise(function(y) quantile(y,
seq(0, 1, by = 0.01), na.rm = TRUE))(df2), stringsAsFactors = FALSE)
ncol(df3)
})
lst5 <- split(names(df1)[-1], gsub(".*\\_", "", names(df1)[-1]))
lapply(seq_along(lst5), function(i) {
df2 <- df1[, lst5[[i]]]
df3 <- data.frame(Percentiles = paste0(seq(0, 100, by = 1), "%"),
numcolwise(function(y) quantile(y,
seq(0, 1, by = 0.01), na.rm = TRUE))(df2), stringsAsFactors = FALSE)
write.csv(df3, paste0(paste(getwd(), "final", paste(names(lst4)[[i]],
"Quantile",
sep = "_"), sep = "/"), ".csv"), row.names = FALSE, quote = FALSE)
})
ReadOut1 <- lapply(list.files(recursive = TRUE)[grep("Quantile",
list.files(recursive = TRUE))],
function(x) read.csv(x, header = TRUE, stringsAsFactors = FALSE))
dir.create("Indices")
sapply(ReadOut1, dim)[,1:3] ##different dimensions
# [,1] [,2] [,3]
#[1,] 101 101 101
#[2,] 157 258 258
names1 <- unlist(lapply(ReadOut1, function(x) names(x)[-1]))
names2 <- gsub("\\_.*", "", names1)
names3 <- unique(gsub("[.]", " ", names2))
length(names3)
#[1] 264
#lstNew <- simplify2array(ReadOut1) ###results you got
# nrow(lstNew)
#NULL####
ReadOut2 <- lapply(seq_along(ReadOut1),function(i) {df2 <- ReadOut1[[i]]; df3
<-as.data.frame(matrix(NA,nrow=101,ncol=length(names3), dimnames=list(NULL,
names3))); names(df2) <- gsub("[.]"," ", gsub("\\_.*","", names(df2))); df2 <-
df2[,-1]; df3[,match(names(df2), names(df3))] <- df2; df3})
lstNew <- simplify2array(ReadOut2)
nrow(lstNew)
#[1] 264
lapply(1:nrow(lstNew), function(i) { dat1 <- data.frame(Percentiles =
paste0(seq(0, 100, by = 1), "%"), do.call(cbind, lstNew[i, ]), stringsAsFactors
= FALSE); colnames(dat1) <- c("Percentiles", paste(names(lst3),
rep(rownames(lstNew)[i],length(lst3)),sep="_"));
write.csv(dat1,paste0(paste(getwd(), "Indices", gsub(" ",
"_",rownames(lstNew)[i]), sep="/"),".csv"),row.names=FALSE, quote=FALSE)})
## Output2:
ReadOut2 <- lapply(list.files(recursive = TRUE)[grep("Indices",
list.files(recursive = TRUE))],
function(x) read.csv(x, header = TRUE, stringsAsFactors = FALSE))
length(ReadOut2)
#[1] 264
ReadOut2[[1]][1:3,1:3]
# Percentiles G100_pav.ANN G101_pav.ANN
#1 0% 0.766900 0.96240
#2 1% 0.796132 0.96572
#3 2% 0.825364 0.96904
______________________________________________
[email protected] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
