unmarked (version 1.0.1)

unmarkedFrame-class: Class "unmarkedFrame"

Description

Methods for manipulating, summarizing and viewing unmarkedFrames

Objects from the Class

Objects can be created by calls to the constructor function unmarkedFrame. These objects are passed to the data argument of the fitting functions.

Slots

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"

Methods

[

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"): ...

coordinates

signature(object = "unmarkedFrame"): extract coordinates

getY

signature(object = "unmarkedFrame"): extract y matrix

numSites

signature(object = "unmarkedFrame"): extract M

numY

signature(object = "unmarkedFrame"): extract ncol(y)

obsCovs

signature(object = "unmarkedFrame"): extract observation-level covariates

obsCovs<-

signature(object = "unmarkedFrame"): add or modify observation-level covariates

obsNum

signature(object = "unmarkedFrame"): extract number of observations

obsToY

signature(object = "unmarkedFrame"):

obsToY<-

signature(object = "unmarkedFrame"): ...

plot

signature(x = "unmarkedFrame", y = "missing"): visualize response variable. Takes additional argument panels which specifies how many panels data should be split over.

projection

signature(object = "unmarkedFrame"): extract projection information

show

signature(object = "unmarkedFrame"): view data as data.frame

siteCovs

signature(object = "unmarkedFrame"): extract site-level covariates

siteCovs<-

signature(object = "unmarkedFrame"): add or modify site-level covariates

summary

signature(object = "unmarkedFrame"): summarize data

See Also

unmarkedFrame, '>unmarkedFit, unmarked-package

Examples

# NOT RUN {
# Organize data for pcount()
data(mallard)
mallardUMF <- unmarkedFramePCount(mallard.y, siteCovs = mallard.site,
	obsCovs = mallard.obs)


# Vizualize it
plot(mallardUMF)

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



# }