Hello,
Something like this?
d <- myframe2$distance
n <- length(d)
mu <- rep(NA, n - 1)
mu[n - 1] <- m <- mean(d[(n - 1):n])
s <- sd(d[(n - 1):n])
ex <- 0
for(i in rev(seq_len(n))[-(1:2)]){
if(d[i] < m + s){
ex <- 0
mu[i] <- m
}else{
ex <- ex + 1
if(ex >= 2) break
}
m <- mean(d[i:n])
s <- sd(d[i:n])
}
mu
Hope this helps,
Rui Barradas
Em 17-12-2012 14:55, Tagmarie escreveu:
Hello everyone,
I have a data frame somewhat like this one:
myframe <- data.frame (Timestamp=c( "24.09.2012 06:00", "24.09.2012 07:00",
"24.09.2012 08:00",
"24.09.2012 09:00", "24.09.2012 10:00",
"24.09.2012 11:00",
"24.09.2012 12:00", "24.09.2012 13:00",
"24.09.2012 14:00"),
distance =c(9,9,9,4,5,9,4,5,5 ) )
myframestime <- as.POSIXct (strptime(as.character(myframe$Timestamp),
"%d.%m.%Y %H:%M"), tz="GMT")
myframe2 <- cbind (myframestime, myframe)
myframe2$Timestamp <- NULL
myframe2
This is what I want to do:
1.) calculate the mean and the standard deviation for "distance" from the
last too rows (at 13:00 and 14:00)
2.) compare the value for distance one row earlier (12:00). If that value is
in the range of the previously calculated mean + sd I want to include the
value and calculate a new mean and a new sd. If there is one value which is
not in the range I want to exclude/ignore the value. If there are two
subsequent values which are not in the range then I want to stopp the
calculation (or at least mark the point by including e.g. NAs).
Does anyone know how to do that?
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