transect.pwr | R Documentation |
Taking a single set of transects from a HiDef digital aerial survey will compute the statistical power for detecting population change.
transect.pwr(
CC,
Species,
nseq = NULL,
t.space,
kseq = seq(0, -1, by = -0.1),
nSim = 10000,
plot = TRUE,
by.density = FALSE,
alternative = "two.sided"
)
CC |
An sf object. The opened cent count shapefile to process |
Species |
A vector. The vector of species (using the two letter code) that will be tested. E.G., c("S_CX","S_SP","S_RH","S_GN","S_GD","S_CA") |
nseq |
A vector (optional). The number of transects to test. If NULL then the code will test a halving, a doubling, and 1.5 times the spacing of the original transects. |
t.space |
Numeric. A value representing the transect spacing in the cent count. |
kseq |
Numeric sequence. Defaults to seq(0,1,by=0.1). The vector of effect sizes to test (i.e., the statistical power is to be tested). |
nSim |
Number of simulations to run power analysis on. |
plot |
Boolean. Whether or not to plot the output in the console. A plot will be returned in the output list. |
by.density |
Boolean. If TRUE, will use density rather than count |
alternative |
indicates the alternative hypothesis and must be one of "two.sided" (default), "less", or "greater". You can specify just the initial letter of the value, but the argument name must be given in full. See ‘Details’ of stats::ks.test() for the meanings of the possible values. |
A list. Contains plotobj (the plot as a ggplot), powervals (the data frame with power values), and samplesize (the sample sizes as a data frame)
CentCount <- "D:/Power_Analysis/Data/Zone113_M02_S01_21_Output/Zone113_M02_S01_21_Output-CentCount.shp"
## Read the CentCount and convert to a data frame
CC <- sf::st_read(CentCount)
## Create the sequences of the original population (effect size)
kseq <- seq(0,-1,by=-0.1)
## Create the number of transects to test
nseq <- c(21,43,64,86)
labs <- c("5km","2.5km","1.68km","1.25km")
names(nseq) <- labs
Species <- c("S_CX","S_SP","S_RH","S_GN","S_GD","S_CA")
poweranalysis <- transect.pwr(CC=CC,Species = Species,nseq = nseq,kseq = kseq,t.space = 2.5,nSim = 1000, plot = TRUE, alternative = "less")
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