Movatterモバイル変換

Pipe operator

Description

Seemagrittr::%>% for details.

Usage

lhs %>% rhs

Arguments

Value

The result of callingrhs(lhs).

Czekanowski overlap index

Description

Computes the Czekanowski index of overlap between two relative-frequencyactivity profilesp andq:

1 - \tfrac{1}{2}\sum_i |p_i - q_i|.

Usage

czekanowski_index(p, q)

Arguments

Details

Inputs should be on acomparable scale; if your data are rawcounts, rescale rows to proportions first (seerescale_matrix()).

Value

A single numeric value in [0, 1] where 0 indicates no overlap and1 indicates identical profiles.

Examples

set.seed(1)n <- 6p <- rmultinom(1, 20, rep(1, n))[,1]; p <- p / sum(p)q <- rmultinom(1, 20, rep(1, n))[,1]; q <- q / sum(q)czekanowski_index(p, q)

Example temporal activity dataset

Description

An example dataset of 5 biological identities across 12 time intervals. Valuesrepresent counts of activity events (e.g., detections or captures) perinterval. This dataset is provided for examples and vignettes.

Usage

ex1

Format

A numeric matrix with 5 rows (biological identities) and 12 columns(time intervals):

Rows

Biological identities (bioID1 …bioID5)

Columns

Time intervals (INT1 …INT12)

Values

Counts of activity per identity × interval

Examples

ex1rowSums(ex1)   # total activity per biological identitycolSums(ex1)   # total activity per time interval

Null-model test via ROSARIO algorithm randomization

Description

Generates a null distribution of concurrent temporal niche overlap byrepeatedly randomizing the input matrix withrosario_sample() andrecomputing the mean pairwise overlap (seetemp_overlap()).

Usage

get_null_model(mat, method, nsim = 1000, parallel = FALSE)

Arguments

Details

For"czekanowski", rows are rescaled to proportions internally tosatisfy the index's assumptions. Randomization preserves each row'stemporal autocorrelation by cyclically shifting (and optionally mirroring)its profile; seerosario_sample().

Whenparallel = TRUE, the function callsfuture::plan(multisession)internally so that randomizations are distributed across available localsessions. This means the function overrides any previously setfuture plan.If you need custom control over parallelization (e.g. cluster backends),run the non-parallel mode (parallel = FALSE) and handle parallelismexternally.

Value

A list with components:

observed_niche_overlap

Mean from all possible pairwise comparisons among biological identities format.

p_value

A one-samplet.test object comparing null means to theobserved value (mu = observed).

null_niche_overlap

A tibble/data.frame of simulated mean overlaps(one per randomization).

See Also

temp_overlap(),rosario_sample(),temp_overlap_matrix()

Examples

get_null_model(ex1, method = "pianka", nsim = 10, parallel = FALSE)

Pianka's niche-overlap index

Description

Computes Pianka's symmetric index of overlap between two non-negativeactivity profilesp andq:

\frac{\sum_i p_i q_i}{\sqrt{\left(\sum_i p_i^2\right)\left(\sum_i q_i^2\right)}}.

Usage

pianka_index(p, q)

Arguments

Details

Pianka's index does not require inputs to sum to 1,but both vectors must be non-negative and not all zero.

Value

A single numeric value in [0, 1]; larger values indicate greateroverlap.

Examples

set.seed(1)n <- 10p <- rpois(n, 3); q <- rpois(n, 3)pianka_index(p, q)

Diagram of ROSARIO null-model randomizations

Description

Visualizes the first 10 hypothetical time use distributions produced byrosario() for a single biological identity. Each panel displays onehypothetical time use distribution with its cyclic shift shown in dark grayand its mirror image shown in dark red.

Usage

plot_rosario(numvec, normalize = TRUE, cols = 4)

Arguments

Value

Invisibly, a list with:

• variants — the original list fromrosario(numvec)

• mat2k_plotted — matrix of the plotted variants (min(10, n) × 2k)

• k — number of time bins

• indices_plotted — which variant indices (1..m) were drawn

Examples

one <- c(0,5,0,7,5,13,70,0)plot_rosario(one, cols = 4)

Row-wise rescaling of a matrix to relative frequencies

Description

Divides each row by its row sum so that every row sums to 1 (leavingdimnames intact).

Usage

rescale_matrix(m)

Arguments

Value

A numeric matrix of the same dimension with each row summing to 1.Rows with a zero sum are left unchanged (resulting inNaN if present).

Examples

ex1_rescale <- rescale_matrix(ex1)rowSums(ex1_rescale)

Generate cyclic and mirrored permutations of a time series

Description

For a numeric vector, creates the set of cyclic shifts and theirmirror images (reverse order), preserving shape but changing location alongthe cycle. The suite of vectors and mirrors represent a complete setof possible distributions.

Usage

rosario(numvec)

Arguments

Value

A list of numeric vectors with all the permutations in the time series,including the mirror patterns.

See Also

vec_permutation(),rosario_sample()

Examples

rosario(c(40, 25, 18, 10, 5, 2))

ROSARIO randomization of an assemblage matrix

Description

Randomly permutes each row by a uniform cyclic shift of its columns and,with probability 0.5, reverses the order (mirror image). This kind ofpermutations preserves each biological identity's temporal autocorrelationstructure and niche breadth while randomizing location within the cycle.

Usage

rosario_sample(mat)

Arguments

Value

A numeric matrix of the same dimension asmat, randomized row-wise.

See Also

rosario(),vec_permutation()

Examples

rosario_sample(ex1)

Mean concurrent temporal niche overlap

Description

Computes themean of all pairwise overlaps among rows (biologicalidentities) using the chosen index.

Usage

temp_overlap(mat, method = c("pianka", "czekanowski"))

Arguments

Details

For"czekanowski", rows are automatically rescaled to proportions.

Value

A single numeric value (named by the method) equal to the mean ofthe lower triangle of the pairwise overlap matrix.

See Also

temp_overlap_matrix(),get_null_model()

Examples

temp_overlap(ex1, method = "pianka")temp_overlap(rescale_matrix(ex1), method = "czekanowski")

Convert a square overlap matrix to a tidy pairwise data frame

Description

Tidies a symmetric overlap (or distance) matrix into athree-column tibble/data frame with pairs and values.

Usage

temp_overlap_df(mat)

Arguments

Value

A data frame with columnsitem1,item2, anddistance(terminology followsstats::as.dist()).

Examples

d <- temp_overlap_matrix(ex1)temp_overlap_df(d)

Pairwise temporal niche-overlap matrix

Description

Computes all pairwise overlaps among rows (biological identities) using the chosen index.

Usage

temp_overlap_matrix(mat, method = c("pianka", "czekanowski"))

Arguments

Details

For Czekanowski, supply arow-rescaled matrix (seerescale_matrix()) or usetemp_overlap(), which handles rescaling.

Value

A square symmetric matrix of overlap values with row/colnames copiedfrommat. The first class of the object is set to the method name.

See Also

temp_overlap(),rescale_matrix()

Examples

temp_overlap_matrix(ex1, method = "pianka")ex1_rescale <- rescale_matrix(ex1)temp_overlap_matrix(ex1_rescale, method = "czekanowski")

Plot null-model results for temporal niche overlap

Description

Creates a histogram of simulated mean niche overlap values from a null model(seeget_null_model()) and overlays a dashed vertical line indicating theobserved mean overlap.

Usage

temp_overlap_plot(results)

Arguments

Value

Aggplot2 object displaying the null distribution of overlap valueswith the observed overlap marked.

See Also

get_null_model(),temp_overlap()

Examples

mod <- get_null_model(ex1, method = "pianka", nsim = 100)temp_overlap_plot(mod)

Cyclic permutation (rotate) a numeric vector

Description

Returns a cyclic shift ofnumvec so that positionx becomes the firstelement and the order wraps around the end.

Usage

vec_permutation(numvec, x = 1)

Arguments

Value

A numeric vector of the same length asnumvec, rotated so thatnumvec[x] is first.

Examples

vec_permutation(1:6, 4)  # 4 5 6 1 2 3