sampling.effort {ANTs} R Documentation

## Sampling effort

### Description

Visualize metric variation through period of observations

### Usage

sampling.effort(
df,
col.time,
cumulative = TRUE,
metric = "met.strength",
assoc.indices = FALSE,
actor = NULL,
sym = FALSE,
scan = NULL,
id = NULL,
index = "sri",
...
)


### Arguments

 df a data frame of interactions or associations. col.time an integer or string indicating the column with the time/period information cumulative a bolean, if TRUE, it computes the argument metric declared for each step of periods keeping previous periods metric a string to call an ANTs function of class 'met.XXX'. assoc.indices a bolean, if TRUE, it creates matrices of associations according to argument 'index' and argument 'df' must be a data frame of associations, see df.to.gbi. Otherwise, it creates a matrix of interactions and argument 'df' must be a data frame of interactions type (see df.to.mat). actor an integer or a string indicating the column of the individuals performing the behaviour. This argument must be declared if argument 'assoc.indices' is equal to FALSE. receiver an integer or a string indicating the column of the individuals receiving the behaviour. This argument must be declared if argument 'assoc.indices' is equal to FALSE. sym a boolean if true, interactions or associations are considered symmetric. This argument must be declared if argument 'assoc.indices' is equal to FALSE. scan a numeric or character vector representing one or more columns used as scan factors. This argument must be declared if argument 'assoc.indices' is equal to FALSE. id a numeric or character vector indicating the column holding ids of individuals. index a string indicating the association index to compute: ... additional argument related to the computation of the metric declared. 'sri' for Simple ratio index: x/x+yAB+yA+yB 'hw' for Half-weight index: x/x+yAB+1/2(yA+yB) 'sr' for Square root index:x/sqr((x+yAB+yA)(x+yAB+yB))

### Details

This function allows to visualize metric (nodal and global) variation through periods of observation. Studies have highlighted the need to assess their stability. Metric stability can be assessed by a sigmoide curve reaching a plateau. While the function doesn't give you any statistical test, it allows to visualize if the plateau is reached or not. For this approach, argument cumulative must be set to TRUE.

### Value

A list of two elemnts:

• 'df', a data frame with metric evolution through time

• plot a plot of the metric evolution through time

Sebastian Sosa

### References

Farine, D. R., & Strandburg-Peshkin, A. (2015). Estimating uncertainty and reliability of social network data using Bayesian inference. Royal Society open science, 2(9), 150367.

### Examples

df <- sim.focal.directed
df\$period <- rep(c("a", "b", "c", "d", "e"))
# Node measures non cumulative example
sampling.effort(df, col.time = "period", cumulative = FALSE,

# Node measures cumulative example
sampling.effort(df, col.time = "period", cumulative = TRUE,

# Node measures with extra arguments example
sampling.effort(df, col.time = "period", actor = "actor",

sampling.effort(df, col.time = "period", actor = "actor",

# Example of how to test global network metric with non cumulative version
sampling.effort(df, col.time = "period", cumulative = FALSE,

# Example of how to test global network metric with cumulative version
sampling.effort(df, col.time = "period", cumulative = TRUE,

# Same example with gambit of the group data collection protocol--------
# Node measures non cumulative example
sampling.effort(sim.grp, col.time = "day", cumulative = TRUE,
metric = "met.strength", assoc.indices = TRUE,
scan = c("time", "location"), id = "ID", index = "sri")

# Node measures non cumulative example
sampling.effort(sim.grp, col.time = "day", cumulative = FALSE,
metric = "met.strength", assoc.indices = TRUE,
scan = c("time", "location"), id = "ID", index = "sri" )

# Node measures with extra arguments example
sampling.effort(sim.grp, col.time = "day", cumulative = FALSE,
metric = "met.affinity", assoc.indices = TRUE,
scan = c("time", "location"), id = "ID", index = "sri")

sampling.effort(sim.grp, col.time = "day", cumulative = FALSE,
metric = "met.affinity", assoc.indices = TRUE,
scan = c("time", "location"), id = "ID",
index = "sri", binary = TRUE)

# Example of how to test global network metric with non cumulative version
sampling.effort(df = sim.grp, col.time = "day", cumulative = FALSE,
metric = "met.density",assoc.indices = TRUE,
scan = c("time", "location"), id = "ID", index = "sri")

# Example of how to test global network metric with cumulative version
sampling.effort(df = sim.grp, col.time = "day", cumulative = TRUE,
metric = "met.density", assoc.indices = TRUE,
scan = c("time", "location"), id = "ID", index = "sri")



[Package ANTs version 0.0.16 Index]