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</div><div>Dear forum members</div><div><br></div><div>I had successful use adehabitatHR R package to estimate home ranges for jaguar based on collar data. Now I'm trying to analyse relocations with adehabitatLT package following the vignette (<a href="http://cran.r-project.org/web/packages/adehabitatLT/vignettes/adehabitatLT.pdf">http://cran.r-project.org/web/packages/adehabitatLT/vignettes/adehabitatLT.pdf</a>). But some doubts emerged and if some of you could clarify me I'll be pleased to hear your suggestions.</div>
<div><br></div><div>My collar data have +/- 19% of missing data due to problems related to receiving GPS signal from collar. So, I've filtered the data:</div><div><br></div><div>#re-subseting to exclude rows with no coordinates</div>
<div>coto_nonas2 <- subset(coto, coto$GPS_Latitude != 'NA')</div><div><br></div><div>(1) In your opinion, is this procedure correct?</div><div><br></div><div>Well, after this i've execute</div><div><br></div>
<div><div>#Placing the missing values in the trajectory</div><div># The relocations have been collected daily, but there are many days during which</div><div># this relocation was not possible (storm, lack of field workers, etc.). </div>
<div># We need to add missing values to define a regular trajectory.</div><div># We have to define a reference date that will be used to check that each date in </div><div># the object of class ltraj is separated from this reference by an integer multiple</div>
<div># of the theoretical dt (here, one day), and place the missing values at the times </div><div># when relocations should theoretically have been collected.</div><div><br></div><div>refdata <- strptime('2013-02-13 00:00:00', '%Y-%m-%d %H:%M:%S')</div>
<div><br></div><div># function setNA to place the missing values with theoretical collects every 6 hours</div><div>coto_moves2 <- setNA(coto_moves, refdata, 6, units = 'hour')</div><div><br></div><div># Even when filling the gaps with NAs, the trajectory is still not regular.</div>
<div># The function sett0 can be used to 'round' the timing of the coordinates.</div><div>coto_moves3 <- sett0(coto_moves2, refdata, 6, units = "hour")</div></div><div><br></div><div><br></div><div>And from then, I filled with doubts.</div>
<div>My wawotest returned any correlation among the variables.</div><div><br></div><div><div> dx dy dist</div><div>a 24.6905441 42.29083967 24.6541496</div><div>ea -1.0000000 -1.00000000 -1.0000000</div>
<div>va <a href="tel:403.9675822" value="+14039675822" target="_blank">403.9675822</a> 405.47166447 <a href="tel:409.2888978" value="+14092888978" target="_blank">409.2888978</a></div><div>za 1.2782036 2.14988760 1.2680683</div>
<div>p 0.1005888 0.01578205 0.1023868</div></div><div><br></div><div><br></div><div>(2) should I discretize the the data in space? Or in time?<br>
</div><div><br></div><div>As say in other message in r-sig-geo forum, I'm a begginer and unfortunately working alone. Could you please provide me some guidance with this?<br></div><div>Any suggestions will be appreciated.</div>
<div>Follows attached a snippet of my data and my script if it can be useful.</div><div><br></div><div>Best regards</div><div><br></div></div></div><br clear="all"><div><br></div>-- <br><div dir="ltr"><div style="text-align:left">
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