Description Usage Arguments Details Value See Also Examples

View source: R/unmarkedFrame.R

Constructor for unmarkedFrames.

1 |

`y` |
An MxJ matrix of the observed measured data, where M is the number of sites and J is the maximum number of observations per site. |

`siteCovs` |
A |

`obsCovs` |
Either a named list of |

`obsToY` |
optional matrix specifying relationship between observation-level covariates and response matrix |

`mapInfo` |
geographic coordinate information. Currently ignored. |

unmarkedFrame is the S4 class that holds data structures to be passed to the model-fitting functions in unmarked.

An unmarkedFrame contains the observations (`y`

), covariates
measured at the observation level (`obsCovs`

), and covariates
measured at the site level (`siteCovs`

).
For a data set with M sites and J observations at each site, y is an
M x J matrix. `obsCovs`

and `siteCovs`

are both data frames
(see data.frame). `siteCovs`

has M rows so that each row
contains the covariates for the corresponding sites.
`obsCovs`

has M*obsNum rows so that each covariates is ordered by
site first, then observation number. Missing values are coded with
`NA`

in any of y, siteCovs, or obsCovs.

Additionally, unmarkedFrames contain metadata: obsToY, mapInfo.
obsToY is a matrix describing relationship between response matrix and
observation-level covariates. Generally this does not need to be
supplied by the user; however, it may be needed when using
`multinomPois`

. For example, double observer sampling, y
has 3 columns corresponding the observer 1, observer 2, and both, but
there were only two independent observations.
In this situation, y has 3 columns, but obsToY must be specified.

Several child classes of `unmarkedFrame`

require addional
metadata. For example, `unmarkedFrameDS`

is used to organize
distsance sampling data for the `distsamp`

function, and
it has arguments dist.breaks, tlength, survey, and unitsIn, which
specify the distance interval cut points, transect lengths, "line" or
"point" transect, and units of measure, respectively.

All site-level covariates are automatically copied to obsCovs so that site level covariates are available at the observation level.

an unmarkedFrame object

`unmarkedFrame-class`

,
`unmarkedFrameOccu`

, `unmarkedFramePCount`

,
`unmarkedFrameDS`

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 36 37 | ```
# Set up data for pcount()
data(mallard)
mallardUMF <- unmarkedFramePCount(mallard.y, siteCovs = mallard.site,
obsCovs = mallard.obs)
summary(mallardUMF)
# Set up data for occu()
data(frogs)
pferUMF <- unmarkedFrameOccu(pfer.bin)
# Set up data for distsamp()
data(linetran)
ltUMF <- with(linetran, {
unmarkedFrameDS(y = cbind(dc1, dc2, dc3, dc4),
siteCovs = data.frame(Length, area, habitat),
dist.breaks = c(0, 5, 10, 15, 20),
tlength = linetran$Length * 1000, survey = "line", unitsIn = "m")
})
summary(ltUMF)
# Set up data for multinomPois()
data(ovendata)
ovenFrame <- unmarkedFrameMPois(ovendata.list$data,
siteCovs=as.data.frame(scale(ovendata.list$covariates[,-1])),
type = "removal")
summary(ovenFrame)
## Not run:
# Set up data for colext()
frogUMF <- formatMult(masspcru)
summary(frogUMF)
## End(Not run)
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.