profileCI | R Documentation |
As of version 1.2-0 of Rcapture, this function is deprecated, but kept for back compatibility. Please use closedpCI.t
instead.
The profileCI
function computes the multinomial profile likelihood for the abundance of some closed population
capture-recapture models.
profileCI(X, dfreq=FALSE, m="M0", h="Chao", a=2, mX=NULL, mname="Customized model", neg=TRUE, alpha=0.05) ## S3 method for class 'profileCI' print(x, ...)
X |
The table of the observed capture histories in one of the two accepted formats. In the default format, it has one
row per unit captured in the experiment. In this case, the number of columns in the table represents the number of
capture occasions in the experiment (noted t). In the alternative format, it contains one row per capture
history followed by its frequency. In that case, |
dfreq |
This argument specifies the format of the data matrix |
m |
A character string identifying the model, either "M0"=M0 model, "Mt"=Mt model, "Mh"=Mh model or "Mth"=Mth model. |
h |
A character string ("Chao" = Chao model, "Poisson" = 2^k-1), "Darroch" = (k^2)/2 or a numerical function taking only one argument specifying the form of the column for heterogeneity in the design matrix. |
a |
The value of the exponent's base for a Poisson model. |
mX |
The design matrix of the loglinear model. In this matrix, the order of the capture histories is as defined in the
|
mname |
A character string specifying the name of the customized model. |
neg |
If this option is set to TRUE, negative eta parameters in Chao models are set to zero. |
alpha |
A confidence interval with confidence level 1-alpha is constructed. The value of alpha must be between 0 and 1; the default is 0.05. |
x |
An object, produced by the |
... |
Further arguments passed to or from other methods. |
This function does not work for closed population models featuring a behavioral effect, such as Mb and Mbh.
This function produces a plot of the multinomial profile likelihood for N. The value of N maximizing the profile likelihood and the bounds of the confidence interval are identified. It also produces the following objects :
n |
The number of captured units |
results |
A table containing the abundance estimation and its confidence interval. |
alpha |
1-the confidence level of the interval. |
Louis-Paul Rivest Louis-Paul.Rivest@mat.ulaval.ca and Sophie Baillargeon
Baillargeon, S. and Rivest, L.P. (2007) Rcapture: Loglinear models for capture-recapture in R. Journal of Statistical Software, 19(5), doi: 10.18637/jss.v019.i05.
Cormack, R. M. (1992) Interval estimation for mark-recapture studies of closed populations. Biometrics, 48, 567–576.
closedp
, closedp.mX
, closedp.h
# hare data set profileCI(hare, m = "Mth", h = "Poisson", a = 2) # HIV data set mat <- histpos.t(4) mX2 <- cbind(mat, mat[, 1] * mat[, 2]) profileCI(hare, m = "Mh", h = "Chao")
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