Hi forum members,
I am new here and trying to use RMark to determine the transitions probabilities between two states with the the effect of covariates.But, I got stuck and have been struggling to figure it out.
I have three occasions (time 3) in which first was captured and released with marking, second and third are recapture. Besides these, I have 6 states (startum) I want to determine
1. whether the movement is based on the temp, flow or area: Psi(AB), Psi(AC), … Psi(AF), is it going to depend on temp, flow, and/or area in A or
2. whether this relationship vary with body length.
The example of the data is:
0A0 1 80
0A0 1 86
0A0 1 86
E00 1 80
AF0 1 95
0A0 1 90
A00 1 81
A00 1 84
A00 1 86
A00 1 80
AF0 1 88
0A0 1 89
AF0 1 86
AF0 1 90
AF0 1 92
0A0 1 102
0A0 1 87
0A0 1 93
A00 1 103
A00 1 85
0A0 1 95
A00 1 90
0A0 1 90
A00 1 93
0A0 1 91
A00 1 88
A00 1 112
0A0 1 88
I used the following code
[example<-import.chdata("example",field.names=c("ch", "freq", "length"),
field.type=c("n","n"),header=FALSE)]
# to add the covariates, I used the following code but did not work
mypvars=data.frame(stratum=c("A","B","C","D","E","F"),Area=c(280,150,210,190,65,200),
temperature=c("18","17","18.5","19","17","18"),flow=c("31.5","29.7","21.1","54.2","15.7","49.3"))
# Process data ( this also did not work for me)
ms.pr=process.data(example, begin.time = 2010,model = "Multistrata")
ms.ddl=make.design.data(ms.pr,mypvars)
ms.dd1$p=merge_design.covariates(ms.dd1$p,mypvars)
ms.dd1$S=merge_design.covariates(ms.dd1$p,mypvars)
ms.dd1$Psi=merge_design.covariates(ms.dd1$p,mypvars)
I want to put the following model to calculate transitions probabilities (whether transition between sites is based on temperature, flow, or area or combination of all). But I don't know how I can build the models.
1. Psi+temperature
2. Psi+flow
3. Psi+ Area
4. Psi+temperature+flow+Area
whether this relationship vary with body length.
I am really looking forward to getting your some hints that will help me a lot. I would be very obliged with your help.
Thank you,
shubha