Description Objects from the Class Slots Methods Note See Also Examples
Methods for manipulating, summarizing and viewing unmarkedFrames
Objects can be created by calls to the constructor function
unmarkedFrame
. These objects are passed to the data argument
of the fitting functions.
y
:Object of class "matrix"
obsCovs
:Object of class "optionalDataFrame"
siteCovs
:Object of class "optionalDataFrame"
mapInfo
:Object of class "optionalMapInfo"
obsToY
:Object of class "optionalMatrix"
signature(x = "unmarkedFrame", i = "numeric", j = "missing",
drop = "missing")
: ...
signature(x = "unmarkedFrame", i = "numeric", j = "numeric",
drop = "missing")
: ...
signature(x = "unmarkedFrame", i = "missing", j = "numeric",
drop = "missing")
: ...
signature(object = "unmarkedFrame")
: extract
coordinates
signature(object = "unmarkedFrame")
: extract y matrix
signature(object = "unmarkedFrame")
: extract M
signature(object = "unmarkedFrame")
: extract ncol(y)
signature(object = "unmarkedFrame")
: extract
observation-level covariates
signature(object = "unmarkedFrame")
: add or modify
observation-level covariates
signature(object = "unmarkedFrame")
: extract number of
observations
signature(object = "unmarkedFrame")
:
signature(object = "unmarkedFrame")
: ...
signature(x = "unmarkedFrame", y = "missing")
: visualize
response variable.
Takes additional argument panels
which specifies how many
panels data should be split over.
signature(object = "unmarkedFrame")
: extract
projection information
signature(object = "unmarkedFrame")
: view data as
data.frame
signature(object = "unmarkedFrame")
: extract
site-level covariates
signature(object = "unmarkedFrame")
: add or modify
site-level covariates
signature(object = "unmarkedFrame")
: summarize data
This is a superclass with child classes for each fitting function
unmarkedFrame
, unmarkedFit
,
unmarked-package
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | # Organize data for pcount()
data(mallard)
mallardUMF <- unmarkedFramePCount(mallard.y, siteCovs = mallard.site,
obsCovs = mallard.obs)
# Vizualize it
plot(mallardUMF, addgrid=FALSE, col=heat.colors)
mallardUMF
# Summarize it
summary(mallardUMF)
str(mallardUMF)
numSites(mallardUMF)
numY(mallardUMF)
obsNum(mallardUMF)
# Extract components of data
getY(mallardUMF)
obsCovs(mallardUMF)
obsCovs(mallardUMF, matrices = TRUE)
siteCovs(mallardUMF)
mallardUMF[1:5,] # First 5 rows in wide format
mallardUMF[,1:2] # First 2 observations
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