Some statistic of the data:
Min. 1st Qu. Median Mean 3rd Qu. Max.0.422 0.727 1.070 1.022 1.280 5.280
The first figure show the histogram of the dataset. The mode is around 0.4~0.5 ms. But the median is around 1 ms. The second figure shows the estimated density function. More work is needed to get the analytical expression of this distribution.
Actually, I think it is possible to deduce the exact pdf by analogue to existing pdf's. For example, as per wikipedia, a poisson pdf is best used for "describing the occurrence of the certain event in a certain time". So it should be possible to find a pdf that "describe the time it takes for a random event to finish".
#This file get the raw data setwd('/your dir') if (file.exists('modem.csv')){ file.remove('modem.csv') } beginTime <- Sys.time() #Store the beginning of the program time <- beginTime for (i in 1:10000) { time <- Sys.time() ##23.1.169.145 att website c <- system('ping -c 1 192.168.1.254', intern = TRUE) len <- length(c) # The last 4 lines only gives stat information data <- c[2:(len-4)] timeStart <- regexpr("time",data, perl = TRUE) timeStop <- regexpr(" ms",data, perl =TRUE) elapse <- substr(data,timeStart+5,timeStop-1) #Ping time elapse result <- cbind(time, elapse) write.table(result, sep=",", file='modem.csv', row.names=FALSE, append = TRUE,col.names = FALSE) }
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