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Error in makegkParallelcpp(as.integer(object$detectfn), as.integer(.openCRstuff$sigmai[type]), :
argument "mask" is missing, with no default
Unconditional SECR models do not produce this error. My question is whether this error correctly prevents estimation of derived parameters from conditional models, or whether this is a bug. I think derived parameters can be estimated from a conditional model, and hence I suspect this error is a bug. Apologies if I am wrong.
Here is a minimal working example using the ovenbird data:
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fit <- openCR.fit(ovenCH, type="JSSAsecrbCL", mask=ovenmask)
Warning message:
In openCR.fit(ovenCH, type = "JSSAsecrbCL", mask = ovenmask) :
multi-session mask provided; using first
> fit
openCR.fit( capthist = ovenCH, type = JSSAsecrbCL, mask = ovenmask )
openCR 2.0.2, 13:42:36 07 Jun 2021
elapsed time 0.275 minutes
N animals : 70
N detections : 192
N sessions : 5 (secondary 49)
Intervals : 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
Analysis type : JSSAsecrbCL
Model : lambda0~1 phi~1 b~1 sigma~1
Fixed (real) : none
Movement model : static
N parameters : 4
Log likelihood : -1324.635
AIC : 2657.271
AICc : 2657.886
Parameter Link
lambda0 log
phi logit
b mlogit
sigma log
Beta parameters (coefficients)
beta SE.beta lcl ucl
lambda0 -3.9477323 0.14309045 -4.2281845 -3.6672802
phi 0.1555693 0.24528045 -0.3251715 0.6363102
b -0.8188841 0.29428890 -1.3956798 -0.2420885
sigma 4.6398200 0.08367938 4.4758115 4.8038286
Eigenvalues : 1 0.23694 0.09405 0.05784
Numerical rank of Hessian : 4 ( svtol = 1e-05 )
<REMAINING OUTPUT CLIPPED>
> derived(fit)
Error in makegkParallelcpp(as.integer(object$detectfn), as.integer(.openCRstuff$sigmai[type]), :
argument "mask" is missing, with no default
Here is the unconditional model:
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> fit <- openCR.fit(ovenCH, type="JSSAsecrb", mask=ovenmask)
Warning message:
In openCR.fit(ovenCH, type = "JSSAsecrb", mask = ovenmask) :
multi-session mask provided; using first
> derived(fit)
Total number observed 70
Parameters in model lambda0, phi, b, superD, sigma
Superpopulation density 2.041739 per ha
Session-specific counts and estimates:
stratum session n R m r z time lambda0 phi b superD sigma lambda f gamma D
1 1 20 20 0 12 0 0 0.0193 0.5388 0.3618 2.042 103.5 0.9797 0.4409 NA 0.7388
1 2 22 22 9 10 3 1 0.0193 0.5388 0.1595 NA 103.5 0.9889 0.4500 0.5500 0.7238
1 3 26 26 12 6 1 2 0.0193 0.5388 0.1595 NA 103.5 0.9939 0.4551 0.5449 0.7157
1 4 19 19 4 5 3 3 0.0193 0.5388 0.1595 NA 103.5 0.9967 0.4579 0.5421 0.7114
1 5 16 15 8 0 0 4 0.0193 NA 0.1595 NA 103.5 NA NA 0.5406 0.7090