trying simple secr.fit but not working

[Joanna Burgar]

Hello,

I am trying to analyse data from 3-4 occasions within multiple sessions of individuals caught in traps but when I try to run secr.fit I receive the following error messages:

> fsecr1 <- secr.fit(capturedata, model = list(D ~ 1, g0 ~ 1, sigma ~ 1), buffer = 10000, mask=grid)

Checking data 

Preparing detection design matrices 

Preparing density design matrix 

Finding initial parameter values... 

Warning messages:

1: In autoini(ch, msk, binomN = details$binomN, ignoreusage = details$ignoreusage) :

  could not calculate 'dbar'; using detector spacing

2: In secr.fit(capturedata, model = list(D ~ 1, g0 ~ 1, sigma ~ 1),  :

  'secr.fit' failed because initial values not found (data sparse?); specify transformed values in 'start'

I'm at a loss at to what to do but imagine it is something quite simple.  Has anyone else run into this issue? I have attached my capturedata and grid files (x and y, respectively, in quenda_data.RData) as well as my code (SCR_quenda_BAJ.R).

Any help is much appreciated!

Thanks,

Joanna

[Murray Efford]

Hi
Please work on providing a clean example - it's frustrating to trace where your data and habitat mask come from. I suspect your mask is wrong. Why not use make.mask?
Murray

[Murray Efford]

Also, please be sure you are using the current version of secr.

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[Murray Efford]

As far as I can tell, you have only 2 recaptures in the entire study, and none in first 5 sessions (autoini uses session 1 by default). Time to give up?

A lot of your code is not needed.

library(secr) # to run ML density in secr
ftraps <- read.csv("TDF.csv") # read in Trap Deployment File as data frame
names(ftraps)[2:3] <- c('x','y')  # not easting, northing
qtraps <- read.traps(data = ftraps)  # DEFAULT detector = "multi"
EDF <- read.csv("EDF.csv") # read in Encounter Data File
head(EDF) # view structure of EDF file
quendaEDF <- EDF[,c(1,4,2,3)]    # reorder columns; NOTE COMMA; already dataframe
quendacapt <- make.capthist(quendaEDF, qtraps, fmt="trapID", noccasions = 51)
summary(quendacapt, terse = TRUE) #17 sessions
## only 2 recaptures, in sessions 6, 17
mask <- make.mask(qtraps, spacing = 20) # DEFAULT buffer = 100; use traps object as template
quenda.secr0 <- secr.fit(quendacapt, model=list(D~1, g0~1, sigma~1), mask=mask)