SDLfilter2.3.3 package

Filtering and Assessing the Sample Size of Tracking Data

asymptote

Horizontal asymptotes of rational functions

boot_area

Cumulative analysis of collective areas by bootstrapping

boot_overlap

Bootstrap overlaps between Utilisation Distributions (UDs)

combn_overlap

Quantifying overlaps between all possible combination of Utilisation D...

ddfilter

Filter locations using a data driven filter

ddfilter_loop

Filter locations by quality index, inner angle, and speed

ddfilter_speed

Filter locations by speed

depthfilter

Filter locations by water depth

distfilter

Filter locations by distance

dupfilter

Filter temporal and/or spatial duplicates

dupfilter_exact

Filter temporally and spatially exact duplicates

dupfilter_qi

Filter temporal duplicates by quality index

dupfilter_space

Filter spatial duplicates

dupfilter_time

Filter temporal duplicates

percent_vol

UD percent volume

to_map

Plot location data on a map

track_param

Calculate parameters between locations

vmax

Maximum linear speed

vmaxlp

Maximum one-way linear speed of a loop trip

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Functions to filter GPS/Argos locations, as well as assessing the sample size for the analysis of animal distributions. The filters remove temporal and spatial duplicates, fixes located at a given height from estimated high tide line, and locations with high error as described in Shimada et al. (2012) <doi:10.3354/meps09747> and Shimada et al. (2016) <doi:10.1007/s00227-015-2771-0>. Sample size for the analysis of animal distributions can be assessed by the conventional area-based approach or the alternative probability-based approach as described in Shimada et al. (2021) <doi:10.1111/2041-210X.13506>.

  • Maintainer: Takahiro Shimada
  • License: GPL-2 | file LICENSE
  • Last published: 2023-11-10

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