On Fri, 18 May 2018 11:47:25 -0500
Ed Siefker wrote:
> I have dose response data analyzed with the package 'drc'.
> 'summary(mymodel)' prints my kinetic parameters. I want
> that text in an ASCII text file. I want to get exactly what I
> would get if I copied and pasted from the terminal window
Your description does not indicate that you know what theory you want to apply
to this data, and this mailing list is the wrong place to discuss which theory
you want to apply.
However, this sounds perfectly suitable to many time series or data frame based
analytical methods. You may need to re
Hi All,
I am having very high-frequency data, captured between 3 to 7 seconds by
sensor for tank. Number of rows of data point are 7 million and its
multivariate problem.
Due to high frequency data, time series is unable to capture frequency &
Cycle of data.
Please help me, how to approach and
Dear all,
I need to simulate data which fit to a double poisson time series model
with certain parameters. Then, check whether the estimated parameter close
to the true parameter by using maximum likelihood estimation.
Simulation:
set.seed(10)
library("rmutil")
a0 = 1.5; a1 = 0.4; b1
Hi!
How about this:
--- snip --
for (i in 1:(length(split_str)-1)) {
assign(paste("DF",i,sep=""),DF[
c((which(DF$name==split_str[i])+1):(which(DF$name==split_str[i+1])-1)),
])
}
--- snip ---
'assign' creates for each subset a new data.frame DFn, where n ist a
count (1,2,...).
But note: i
Forgot to take care of the boundary conditions:
# revised data.frame to take care of boundary conditions
DF = data.frame(name = c('b', 'a','v','z', 'c','d'), val = 0); DF
## name val
## 1b 0
## 2a 0
## 3v 0
## 4z 0
## 5c 0
## 6d 0
split_str = c('a', 'c')
# If
...
yes, but note that:
which(data[[col]] %in% s
can be replaced directly by match:
match(data[[col]], s)
Corner cases (nothing matches, etc.) would also have to be checked and
probably should sort the matched row numbers for safety.
Cheers,
Bert
Bert Gunter
"The trouble with having an open
DF = data.frame(name = c('a', 'v', 'c'), val = 0); DF
## name val
## 1a 0
## 2v 0
## 3c 0
split_str = c('a', 'c')
# If we assume that the values in split_str are ordered in the same order
as in the dataframe, then this might work.
offsets <- match(split_str, DF$name)
# Since yo
Hello,
Maybe something like the following.
splitDF <- function(data, col, s){
n <- nrow(data)
inx <- which(data[[col]] %in% s)
lapply(seq_along(inx), function(i){
k <- if(inx[i] < n) (inx[i] + 1):(inx[i + 1])
data[k, ]
})
}
splitDF(DF, "name", split_str)
Hope t
Hi,
I am struggling to split a data.frame as will below scheme :
DF = data.frame(name = c('a', 'v', 'c'), val = 0); DF
split_str = c('a', 'c')
Now, for each element in split_str, R should find which row of DF contains
that element, and return DF with all rows starting from next row of the
corre
Hi lily,
You could also create "blackcells" as a dataframe (which is itself a
type of list). I used a list as I thought it would be a more general
solution if there were different numbers of values for different grid
cells. The use of 1 for the comparison was due to the grid increments
being 1. If
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