Do you know the error for each record? Then you could do date calculations on the GPS (maybe GPX ?) files in Python or any other scripting language. I do not know if R has proper date calculation methods, but most probably it has. If the format of the GPS logs fits, this could even de done in spreadsheet software like Excel or Calc. If you want actual code as an answer, you would need to elaborate on the exact format of your GPS logs...

Dear Christian thanks for the comment. The error is not constant and we can't expect specific frequency. The interval is 1 minute but in most records it has an error of between 5 and 15 seconds.

To read a file using python you can use this code. Then you can modify X or Y values. If you need the complete code I can send to you

***********************************************************

#! /usr/bin/env python

# -*- coding: utf-8

import csv

x,y = [],[]

csv_reader = csv.reader(open('data.csv'))

for line in csv_reader:

x.append(float(line[0]))

y.append(float(line[1]))

***********************************************************

Dear Jose I am not sure if you understood my problem. I have thousands of GPS files and I think I cannot modify the values before I know how to calculate the time error.

Oh....I understood you know the error and need to aply a correction.

I don't quite understand the question. If you don't know the errors, you're stuck. If you do know the errors, just add the appropriate number of seconds to the R time object.

Try using numberAsPOSIXct() from the oce package, exemplified below. Note: R is formatting the fractional seconds by rounding to multiples of 0.2, despite my setting of the digits for seconds. But the as.numeric() call indicates that the values have been properly created.

Researchgate doesn't seem to have a way to indicate code (really? can that really be true???) so I will enclose my code in html tokens to help (I hope).

> library(oce)

> ## the start of July 1st, 2001 (Canada Day)

> t options(digits.secs=4)

> options(digits=14)

> tt t

[1] "2010-07-01 UTC"

> tt

[1] "2010-07-01 00:00:00.0 UTC" "2010-07-01 00:00:00.0 UTC" "2010-07-01 00:00:00.2 UTC" "2010-07-01 00:00:00.2 UTC"

[5] "2010-07-01 00:00:00.4 UTC" "2010-07-01 00:00:00.5 UTC"

> as.numeric(tt)

[1] 1277942400.0 1277942400.1 1277942400.2 1277942400.3 1277942400.4 1277942400.5

I have had the same problems with hourly GPS-data and solved it using adehabitatLT in R. Look into the manual of adehabitatLT section 3.4. The functions setNA() and sett0() can be used to round the time in your trajectories.