Skip to contents

Bootstrap confidence interval for a mean direction

Source: R/circular_statistics.R
boot_mean_ci.Rd

Computes a nonparametric bootstrap confidence interval for the mean direction of each group, resampling angles with replacement and taking the percentiles of the bootstrap mean directions (centred on the sample mean). Unlike the normal-approximation interval from vonmises_fit, it makes no distributional assumption and stays usable at low concentration or small sample size, where that approximation is unreliable.

Usage

boot_mean_ci(
  hd,
  group_col = NULL,
  angle_col = "heading",
  conf = 0.95,
  R = 999L,
  axial = FALSE
)

Arguments

hd

Data frame containing headings in radians.

group_col

Column(s) to group by. NULL (default) treats the whole data frame as one group.

angle_col

Name of the heading column. Default "heading".

conf

Confidence level. Default 0.95.

R

Number of bootstrap resamples. Default 999. Set the RNG seed with set.seed for reproducible intervals.

axial

Logical; when TRUE, treat the angles as axial (bidirectional, mod-pi): mu/mu_deg are the mean axis in \([0, \pi)\) and the interval is scaled accordingly. Default FALSE (directional).

Value

Data frame with columns group_col (if supplied), mu (mean direction, radians), mu_deg (degrees), ci_lo and ci_hi (conf-level bootstrap interval on mu, radians; bounds may fall outside \([0, 2\pi)\) to describe an arc), resultant_R, and n. Groups with fewer than two finite angles yield an all-NA interval.

See also

vonmises_fit, circ_dispersion

Examples

hd <- derive_headings(cpunctatus, rule = "distal", carry = "arc")
set.seed(1)
boot_mean_ci(hd, group_col = "arc", R = 199)
#>   arc        mu    mu_deg      ci_lo    ci_hi resultant_R  n
#> 1  10 1.3766939  78.87875 -1.4921571 3.812127  0.07055967 29
#> 2  15 0.7363627  42.19048 -0.6126016 1.996328  0.24477975 30
#> 3  20 3.8069634 218.12293  1.3390950 6.357445  0.07326231 27
#> 4  30 5.9212227 339.26107  4.3594085 8.083512  0.12936762 37
#> 5  40 3.5642725 204.21777  0.6403791 6.238911  0.06536414 20
#> 6  50 1.5873930  90.95092 -0.3378658 4.424066  0.15790182 26
#> 7   5 2.4205480 138.68719 -0.4536937 5.257315  0.07181952 31
#> 8   0 3.0747577 176.17064  1.4943839 4.453216  0.23531457 35