`unmarkedFrame.Rd`

Constructor for unmarkedFrames.

unmarkedFrame(y, siteCovs=NULL, obsCovs=NULL, mapInfo, obsToY)

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

# Set up data for pcount() data(mallard) mallardUMF <- unmarkedFramePCount(mallard.y, siteCovs = mallard.site, obsCovs = mallard.obs) summary(mallardUMF)#> unmarkedFrame Object #> #> 239 sites #> Maximum number of observations per site: 3 #> Mean number of observations per site: 2.76 #> Sites with at least one detection: 40 #> #> Tabulation of y observations: #> 0 1 2 3 4 7 10 12 <NA> #> 576 54 11 9 6 1 1 1 58 #> #> Site-level covariates: #> elev length forest #> Min. :-1.436000 Min. :-4.945000 Min. :-1.2650000 #> 1st Qu.:-0.956500 1st Qu.:-0.563000 1st Qu.:-0.9560000 #> Median :-0.198000 Median : 0.045000 Median :-0.0650000 #> Mean :-0.000046 Mean :-0.000029 Mean : 0.0000669 #> 3rd Qu.: 0.994000 3rd Qu.: 0.626000 3rd Qu.: 0.7900000 #> Max. : 2.434000 Max. : 2.255000 Max. : 2.2990000 #> #> Observation-level covariates: #> ivel date #> Min. :-1.75300 Min. :-2.90400 #> 1st Qu.:-0.66600 1st Qu.:-1.11900 #> Median :-0.13900 Median :-0.11900 #> Mean : 0.00002 Mean : 0.00007 #> 3rd Qu.: 0.54900 3rd Qu.: 1.31000 #> Max. : 5.98000 Max. : 3.81000 #> NA's :52 NA's :42# 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$Length * 1000, survey = "line", unitsIn = "m") }) summary(ltUMF)#> unmarkedFrameDS Object #> #> line-transect survey design #> Distance class cutpoints (m): 0 5 10 15 20 #> #> 12 sites #> Maximum number of distance classes per site: 4 #> Mean number of distance classes per site: 4 #> Sites with at least one detection: 11 #> #> Tabulation of y observations: #> 0 1 2 3 4 5 6 8 #> 14 9 10 4 2 4 3 2 #> #> Site-level covariates: #> Length area habitat #> Min. :1 Min. :3.873 A:6 #> 1st Qu.:3 1st Qu.:4.473 B:6 #> Median :4 Median :5.426 #> Mean :4 Mean :5.351 #> 3rd Qu.:5 3rd Qu.:6.027 #> Max. :7 Max. :7.059# Set up data for multinomPois() data(ovendata) ovenFrame <- unmarkedFrameMPois(ovendata.list$data, siteCovs=as.data.frame(scale(ovendata.list$covariates[,-1])), type = "removal") summary(ovenFrame)#> unmarkedFrame Object #> #> 70 sites #> Maximum number of observations per site: 4 #> Mean number of observations per site: 4 #> Sites with at least one detection: 44 #> #> Tabulation of y observations: #> 0 1 2 3 #> 218 49 11 2 #> #> Site-level covariates: #> ufc trba #> Min. :-1.4713 Min. :-2.0099 #> 1st Qu.:-0.7408 1st Qu.:-0.6931 #> Median :-0.2535 Median :-0.1287 #> Mean : 0.0000 Mean : 0.0000 #> 3rd Qu.: 0.9844 3rd Qu.: 0.7178 #> Max. : 2.3444 Max. : 2.8811