While I'm no stranger to all sorts of errors on my secr journey, I've come upon a new one having to do with the buffer and bias check. I've been getting errors like:
(1)
- Code: Select all
Warning message:
In bufferbiascheck(output, buffer, biasLimit) :
predicted relative bias exceeds 0.01 with buffer = 15000
and..
(2)
- Code: Select all
Warning message:
In bufferbiascheck(output, buffer, biasLimit) :
could not perform bias check
> secr.fit(Overberg_90_Phase1, model=list(g0 ~ b, g0 ~ T), CL=FALSE, trace = FALSE, buffer=20000, verify = FALSE)
Error in nlsModel(formula, mf, start, wts) :
singular gradient matrix at initial parameter estimates
In addition: Warning messages:
1: In secr.fit(Overberg_90_Phase1, model = list(g0 ~ b, g0 ~ T), CL = FALSE, :
at least one variance calculation failed
2: In bias.D(buffer, temptrps, detectfn = output$detectfn, detectpar = dpar, :
bias.D() does not allow for variable effort (detector usage)
all having to do something with bias issues. I did some homework on the bias.D command and suggest.buffer, but I didn't get very far with those script without running into other questions and errors.
Can anyone explain what is possibly wrong in my data or script to get this error? What must I look to fix in my script? The first warning above saying "predicted relative bias exceeds 0.01 with buffer = 15000" didn't change no matter what buffer I tried... whether it was 1000 or 30,000!?
Through dumb luck, I'm gotten past the second set of errors and warnings but still getting bufferbiascheck warnings and my density results are definitely a bit to high to be right!
Any thoughts or guidance would be amazing!!!
Thanks in advance,
Carolyn