dht2 for stratified abundance estimates derived from mrds model

[Evan Curtis]

Hi all,

I have mark-recapture distance-sampling aerial survey data temporally stratified within a region of interest. Specifically, there are 12 replicate surveys within the 1 region of interest. Each replicate survey has 4 transects.

I've identified the following mrds ddf() model:

MRDS.6a=ddf(

  dsmodel=~mcds(key="hn",formula=~side+obsname),

  mrmodel=~glm(~obsname + size),

  data=survey.data,

  method="io",

  meta.data=list(binned=TRUE,point=FALSE,width=300,

  breaks=c(0,50,100,200,300)))

I want to derive abundance and variance estimates with respect to each replicate survey using the ddf() model outlined above. I use dht2():

FG.roo.MRDS <- dht2(ddf = MRDS.6a,

                    flatfile = flatfile.mrds,

                    stratification = "effort_sum",

                    strat_formula = ~Rep,

                    er_est = "R2",

                    ci_width = 0.95)

my flatfile contains all five essential columns + the three covariates used in the mrds model. The error I can't get past when running the dht2() model is:

Error in if (ddf$ds$aux$point) "point" else "line" : 

  argument is of length zero

I'm uncertain about where or how to actually specify this information when using ddf(). There are two things I could think of that could be causing the error...

1. My ddf() model does have a similar ?'slot'? but it's address is:

MRDS.6a[["ds"]][["ds"]][["aux"]][["point"]]

2. There are duplicate observations in the flatfile (because observer name is a covariate and it is a mark-recapture model).

All suggestions much appreciated. Thanks in advance!

Evan

[Eric Rexstad]

Evan

My suspicion about your error message is that dht2​ hasn't been tested with an object containing an mrmodel​ component.  You have already done the detective work to deduce when the dht2​ code goes looking for ddf$ds$aux$point​ it fails to find it.  As you note, the item of interest is in a different location.  Simply toy example (in addition to yours):

library(mrds)

data(book.tee.data)

region <- book.tee.data$book.tee.region

egdata <- book.tee.data$book.tee.dataframe

samples <- book.tee.data$book.tee.samples

obs <- book.tee.data$book.tee.obs

# fit an independent observer model with point independence

result.io <- ddf(dsmodel=~cds(key = "hn"), mrmodel=~glm(~distance),

                 data=egdata, method="io", meta.data=list(width=4))

result.io$ds$ds$aux$point

For now, dht2​ is not usable with models that include an mrmodel​ component.

---

From: 'Evan Curtis' via distance-sampling <distance...@googlegroups.com>
Sent: 23 November 2021 04:03
To: distance-sampling <distance...@googlegroups.com>
Subject: [distance-sampling] dht2 for stratified abundance estimates derived from mrds model

 

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[Evan Curtis]

Thanks once again Eric! 

I'll explore a different analysis option for the mrds replicates.

Evan