Description Usage Arguments Details Value Note See Also Examples

View source: R/unmarkedFrame.R

These functions construct unmarkedFrames for data collected during primary and secondary sampling periods.

1 2 3 4 5 6 | ```
unmarkedMultFrame(y, siteCovs, obsCovs, numPrimary, yearlySiteCovs)
unmarkedFrameGMM(y, siteCovs, obsCovs, numPrimary, yearlySiteCovs, type,
obsToY, piFun)
unmarkedFrameGDS(y, siteCovs, numPrimary, yearlySiteCovs, dist.breaks,
survey, unitsIn, tlength)
unmarkedFrameGPC(y, siteCovs, obsCovs, numPrimary, yearlySiteCovs)
``` |

`y` |
A matrix of the observed data. |

`siteCovs` |
Data frame of covariates that vary at the site level. |

`obsCovs` |
Data frame of covariates that vary within site-year-observation level. |

`numPrimary` |
Number of primary time periods (seasons in the multiseason model). |

`yearlySiteCovs` |
Data frame containing covariates at the site-year level. |

`type` |
Set to "removal" for constant-interval removal sampling, "double" for standard double observer sampling, or "depDouble" for dependent double observer sampling. This should be not be specified for other types of survey designs. |

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

`piFun` |
A function converting an MxJ matrix of detection probabilities into an MxJ matrix of multinomial cell probabilities. |

`dist.breaks` |
see |

`survey` |
see |

`unitsIn` |
see |

`tlength` |
see |

unmarkedMultFrame objects are used by `colext`

.

unmarkedFrameGMM objects are used by `gmultmix`

.

unmarkedFrameGDS objects are used by `gdistsamp`

.

unmarkedFrameGPC objects are used by `gpcount`

.

For a study with *M* sites, *T* years, and a maximum of
*J* observations per site-year, the data can be supplied in a
variety of ways but are stored as follows.
`y`

is an *M by TJ* matrix, with each row
corresponding to a site. `siteCovs`

is a data frame with *M*
rows. `yearlySiteCovs`

is a data frame with *MT* rows which
are in site-major, year-minor order. `obsCovs`

is a data frame
with *MTJ* rows, which are ordered by site-year-observation, so that
a column of `obsCovs`

corresponds to `as.vector(t(y))`

,
element-by-element. The number of years must be specified in
`numPrimary`

.

If the data are in long format, the convenience function
`formatMult`

is useful for creating the unmarkedMultFrame.

unmarkedFrameGMM and unmarkedFrameGDS are superclasses of
unmarkedMultFrame containing information on
the survey design used that resulted in multinomial outcomes. For
unmarkedFrameGMM and constant-interval removal sampling, you can set
type="removal" and ignore
the arguments obsToY and piFun. Similarly, for double-observer sampling,
setting type="double" or type="depDouble" will automatically create an appropiate
obsToY matrix and `piFuns`

. For all other situations, the type
argument of unmarkedFrameGMM should be
ignored and the obsToY and piFun arguments must be specified. piFun must be a
function that converts an MxJ matrix of detection probabilities into an MxJ
matrix of multinomial cell probabilities. obsToY is a matrix describing how
the obsCovs relate to the observed counts y. For further discussion and examples
see the help page for `multinomPois`

and `piFuns`

.

unmarkedFrameGMM and unmarkedFrameGDS objects can be created from an unmarkedMultFrame using the "as" conversion method. See examples.

an unmarkedMultFrame or unmarkedFrameGMM object

Data used with colext, gmultmix, and gdistsamp may be collected during a single year, so yearlySiteCovs may be a misnomer is some cases.

`formatMult`

, `colext`

,
`gmultmix`

, `gpcount`

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 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 | ```
n <- 50 # number of sites
T <- 4 # number of primary periods
J <- 3 # number of secondary periods
site <- 1:50
years <- data.frame(matrix(rep(2010:2013, each=n), n, T))
years <- data.frame(lapply(years, as.factor))
occasions <- data.frame(matrix(rep(1:(J*T), each=n), n, J*T))
y <- matrix(0:1, n, J*T)
umf <- unmarkedMultFrame(y=y,
siteCovs = data.frame(site=site),
obsCovs=list(occasion=occasions),
yearlySiteCovs=list(year=years),
numPrimary=T)
umfGMM1 <- unmarkedFrameGMM(y=y,
siteCovs = data.frame(site=site),
obsCovs=list(occasion=occasions),
yearlySiteCovs=data.frame(year=c(t(years))),
# or: yearlySiteCovs=list(year=years),
numPrimary=T, type="removal")
# A user-defined piFun calculating removal probs when time intervals differ.
instRemPiFun <- function(p) {
M <- nrow(p)
J <- ncol(p)
pi <- matrix(NA, M, J)
p[,1] <- pi[,1] <- 1 - (1 - p[,1])^2
p[,2] <- 1 - (1 - p[,2])^3
p[,3] <- 1 - (1 - p[,3])^5
for(i in 2:J) {
pi[,i] <- pi[, i - 1]/p[, i - 1] * (1 - p[, i - 1]) * p[, i]
}
return(pi)
}
# Associated obsToY matrix required by unmarkedFrameMPois
o2y <- diag(ncol(y))
o2y[upper.tri(o2y)] <- 1
o2y
umfGMM2 <- unmarkedFrameGMM(y=y,
siteCovs = data.frame(site=site),
obsCovs=list(occasion=occasions),
yearlySiteCovs=data.frame(year=years),
numPrimary=T, obsToY=o2y, piFun="instRemPiFun")
str(umfGMM2)
``` |

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