Parameter summaries and model selection

Models evaluated:

model description
sc.fm1 dot model
sc.fm2.0 lure
sc.fm2.1 snow
sc.fm2.2 temp
sc.fm2.3 pass
sc.fm3.0 lure + snow
sc.fm3.1 lure + pass
sc.fm4.0 lure + snow + temp
sc.fm4.2 lure + snow + temp + pass
sc.fm5.0 lure + snow + temp + pass + temp * snow
sc.fm5.1 lure + snow + temp + pass + lure * snow




AmericanMarten



model metadata:

survey n_sites detections rep_period model_aggragate_reps state_buffer iterations burnin thin sigma.mean sigma.sd
SN east side cells 19 46 7 days 300 2.5 350000 20000 20 0.765 0.13



global models:

model covs bayes_p_val bayes_factor revMCMC_constrained revMCMC_unconstrained revMCMC_noInteractions
sc.fm5.0 lure 0.45994 0.216 0.00406 0.0049091 0.0051515
sc.fm5.0 snow 0.99399 0.076 0.00097 0.0006061 0.0013333
sc.fm5.0 temp 0.94442 0.094 0.00212 0.0028485 0.0041212
sc.fm5.0 pass 0.99952 33.049 0 0.1369091 0.0000000
sc.fm5.0 temp*snow 0.54745 0.139 0 0.0043636 NA
sc.fm5.1 lure 0.41709 0.263 0.00406 0.0049091 0.0051515
sc.fm5.1 snow 0.94704 0.075 0.00097 0.0006061 0.0013333
sc.fm5.1 temp 0.48484 0.153 0.00212 0.0028485 0.0041212
sc.fm5.1 pass 0.99839 36.118 0 0.1369091 0.0000000
sc.fm5.1 lure*snow 0.99996 0.110 6e-05 0.0007273 NA



single covariate models:

model covs bayes_p_val bayes_factor revMCMC_constrained revMCMC_unconstrained revMCMC_noInteractions
sc.fm2.0 lure 0.17236 0.589 0.00406 0.0049091 0.0051515
sc.fm2.1 snow 0.38879 0.170 0.00097 0.0006061 0.0013333
sc.fm2.2 temp 0.1195 0.487 0.00212 0.0028485 0.0041212
sc.fm2.3 pass 0.99988 34.540 0 0.1369091 0.0000000



All models: Covariates with p values below .11 (bayesian p, probability covariate is not null)

model covs bayes_p_val bayes_factor revMCMC_constrained revMCMC_unconstrained revMCMC_noInteractions



parameter support:

level support covariates
good pval and rev MCMC
moderate pval or rev MCMC
poor neither lure - snow - temp - pass - snow*temp - lure*snow



models with significant covariates:



waic:

model description WAIC
sc.fm1 dot model 279.4672



Density per 100km, significant models:

## Warning: The `x` argument of `as_tibble.matrix()` must have column names if `.name_repair` is omitted as of tibble 2.0.0.
## Using compatibility `.name_repair`.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.



top models density per 100sq km, significant covariates:

species model covs n_effective mode hdi_89pct_lower hdi_89pct_upper
AmericanMarten sc.fm1 D 277 13.511 5.1 41.35



notes:

Bobcat



model metadata:

survey n_sites detections rep_period model_aggragate_reps state_buffer iterations burnin thin sigma.mean sigma.sd
SN east side cells 19 6 7 days 300 2.5 350000 20000 20 1.175 0.14



global models:

model covs bayes_p_val bayes_factor revMCMC_constrained revMCMC_unconstrained revMCMC_noInteractions
sc.fm5.0 lure 0.59772 0.757 0.00358 0.0034545 0.0049091
sc.fm5.0 snow 0.52387 0.619 0.00164 0.0027273 0.0043636
sc.fm5.0 temp 0.2674 1.142 0.00073 0.0003636 0.0007273
sc.fm5.0 pass 0.99888 35.700 0 0.1543030 0.0000000
sc.fm5.0 temp*snow 0.59192 0.414 0 0.0017576 NA
sc.fm5.1 lure 0.46539 1.025 0.00358 0.0034545 0.0049091
sc.fm5.1 snow 0.30294 1.115 0.00164 0.0027273 0.0043636
sc.fm5.1 temp 0.44471 0.728 0.00073 0.0003636 0.0007273
sc.fm5.1 pass 0.99999 34.591 0 0.1543030 0.0000000
sc.fm5.1 lure*snow 0.51301 0.619 0.00012 0.0012727 NA



single covariate models:

model covs bayes_p_val bayes_factor revMCMC_constrained revMCMC_unconstrained revMCMC_noInteractions
sc.fm2.0 lure 0.51599 0.819 0.00358 0.0034545 0.0049091
sc.fm2.1 snow 0.52225 0.425 0.00164 0.0027273 0.0043636
sc.fm2.2 temp 0.99962 0.146 0.00073 0.0003636 0.0007273
sc.fm2.3 pass 0.99984 29.716 0 0.1543030 0.0000000



All models: Covariates with p values below .11 (bayesian p, probability covariate is not null)

model covs bayes_p_val bayes_factor revMCMC_constrained revMCMC_unconstrained revMCMC_noInteractions



parameter support:

level support covariates
good pval and rev MCMC
moderate pval or rev MCMC
poor neither lure - snow - temp - pass - snow*temp - lure*snow



models with significant covariates:



waic:

model description WAIC
sc.fm1 dot model 60.73971



Density per 100km, significant models:



top models density per 100sq km, significant covariates:

species model covs n_effective mode hdi_89pct_lower hdi_89pct_upper
Bobcat sc.fm1 D 52 2.191 1.7 78.73



notes:

Coyote



model metadata:

survey n_sites detections rep_period model_aggragate_reps state_buffer iterations burnin thin sigma.mean sigma.sd
SN east side cells 19 218 7 days 300 2.5 350000 20000 20 0.865 0.205



global models:

model covs bayes_p_val bayes_factor revMCMC_constrained revMCMC_unconstrained revMCMC_noInteractions
sc.fm5.0 lure 0 75.422 0.55994 0.5954545 0.6605455
sc.fm5.0 snow 0 59.329 0.03103 0.0418788 0.1226667
sc.fm5.0 temp 0.00116 30.901 0.00933 0.0177576 0.0981212
sc.fm5.0 pass 0.99292 30.913 0.00576 0.2321212 0.0729697
sc.fm5.0 temp*snow 0.8335 0.036 0 0.0006667 NA
sc.fm5.1 lure 0.00091 48.959 0.55994 0.5954545 0.6605455
sc.fm5.1 snow 0 47.519 0.03103 0.0418788 0.1226667
sc.fm5.1 temp 0 19.952 0.00933 0.0177576 0.0981212
sc.fm5.1 pass 0.99996 33.949 0.00576 0.2321212 0.0729697
sc.fm5.1 lure*snow 0.29938 0.228 0.0137 0.0110909 NA



single covariate models:

model covs bayes_p_val bayes_factor revMCMC_constrained revMCMC_unconstrained revMCMC_noInteractions
sc.fm2.0 lure 0 328.643 0.55994 0.5954545 0.6605455
sc.fm2.1 snow 0.00309 7.527 0.03103 0.0418788 0.1226667
sc.fm2.2 temp 0.9992 0.023 0.00933 0.0177576 0.0981212
sc.fm2.3 pass 0.99613 34.153 0.00576 0.2321212 0.0729697



All models: Covariates with p values below .11 (bayesian p, probability covariate is not null)

model covs bayes_p_val bayes_factor revMCMC_constrained revMCMC_unconstrained revMCMC_noInteractions
sc.fm2.0 lure 0 328.643 0.55994 0.5954545 0.6605455
sc.fm3.1 lure 0 50.022 0.55994 0.5954545 0.6605455
sc.fm4.0 snow 0 487.710 0.03103 0.0418788 0.1226667
sc.fm4.0 temp 0 34.157 0.00933 0.0177576 0.0981212
sc.fm4.2 snow 0 201.394 0.03103 0.0418788 0.1226667
sc.fm5.0 lure 0 75.422 0.55994 0.5954545 0.6605455
sc.fm5.0 snow 0 59.329 0.03103 0.0418788 0.1226667
sc.fm5.1 snow 0 47.519 0.03103 0.0418788 0.1226667
sc.fm5.1 temp 0 19.952 0.00933 0.0177576 0.0981212
sc.fm4.2 temp 0.00061 28.596 0.00933 0.0177576 0.0981212
sc.fm5.1 lure 0.00091 48.959 0.55994 0.5954545 0.6605455
sc.fm5.0 temp 0.00116 30.901 0.00933 0.0177576 0.0981212
sc.fm4.2 lure 0.00214 28.559 0.55994 0.5954545 0.6605455
sc.fm3.0 lure 0.00285 19.847 0.55994 0.5954545 0.6605455
sc.fm4.0 lure 0.0029 25.277 0.55994 0.5954545 0.6605455
sc.fm2.1 snow 0.00309 7.527 0.03103 0.0418788 0.1226667
sc.fm3.0 snow 0.03125 0.913 0.03103 0.0418788 0.1226667



parameter support:

level support covariates
good pval and rev MCMC lure
moderate pval or rev MCMC
poor neither snow - temp - pass - snow*temp - lure*snow



models with significant covariates:



waic:

model description WAIC
sc.fm2.0 lure 794.4962
sc.fm1 dot model 808.2681



Density per 100km, significant models:



top models density per 100sq km, significant covariates:

species model covs n_effective mode hdi_89pct_lower hdi_89pct_upper
Coyote sc.fm2.0 D 144 23.352 10.20 70.23
Coyote sc.fm2.0 lure 16500 -0.588 -0.85 -0.31



notes:

poor support for snow, temp

WhiteTailedJackrabbit



model metadata:

survey n_sites detections rep_period model_aggragate_reps state_buffer iterations burnin thin sigma.mean sigma.sd
SN east side cells 19 31 7 days 300 2.5 350000 20000 20 0.322 0.094



global models:

model covs bayes_p_val bayes_factor revMCMC_constrained revMCMC_unconstrained revMCMC_noInteractions
sc.fm5.0 lure 0.97036 0.088 0.00085 0.0013939 0.0014545
sc.fm5.0 snow 0.20831 0.748 0.03794 0.0378788 0.0563030
sc.fm5.0 temp 0.22315 0.586 0.00091 0.0016364 0.0021818
sc.fm5.0 pass 0.9924 34.508 0 0.1741212 0.0006061
sc.fm5.0 temp*snow 0.09116 1.661 0 0.1847879 NA
sc.fm5.1 lure 0.87781 0.089 0.00085 0.0013939 0.0014545
sc.fm5.1 snow 0 60.798 0.03794 0.0378788 0.0563030
sc.fm5.1 temp 0.24412 0.572 0.00091 0.0016364 0.0021818
sc.fm5.1 pass 0.99917 34.523 0 0.1741212 0.0006061
sc.fm5.1 lure*snow 0.22799 1.153 0 0.0027879 NA



single covariate models:

model covs bayes_p_val bayes_factor revMCMC_constrained revMCMC_unconstrained revMCMC_noInteractions
sc.fm2.0 lure 0.59936 0.163 0.00085 0.0013939 0.0014545
sc.fm2.1 snow 0.01558 7.486 0.03794 0.0378788 0.0563030
sc.fm2.2 temp 0.56219 0.130 0.00091 0.0016364 0.0021818
sc.fm2.3 pass 0.99786 32.737 0 0.1741212 0.0006061



All models: Covariates with p values below .11 (bayesian p, probability covariate is not null)

model covs bayes_p_val bayes_factor revMCMC_constrained revMCMC_unconstrained revMCMC_noInteractions
sc.fm5.1 snow 0 60.798 0.03794 0.0378788 0.056303
sc.fm4.0 snow 0.00721 16.882 0.03794 0.0378788 0.056303
sc.fm4.2 snow 0.00989 22.859 0.03794 0.0378788 0.056303
sc.fm2.1 snow 0.01558 7.486 0.03794 0.0378788 0.056303
sc.fm3.0 snow 0.03221 3.231 0.03794 0.0378788 0.056303
sc.fm5.0 temp*snow 0.09116 1.661 0 0.1847879 NA



parameter support:

level support covariates
good pval and rev MCMC
moderate pval or rev MCMC snow - temp - snow*temp
poor neither lure - pass- lure*snow



models with significant covariates:



waic:

model description WAIC
sc.fm2.1 snow 155.6620
sc.fm5.0 lure + snow + temp + pass + temp * snow 156.0913
sc.fm1 dot model 162.3660
sc.fm2.2 temp 163.7429



Density per 100km, significant models:



top models density per 100sq km, significant covariates:

species model covs n_effective mode hdi_89pct_lower hdi_89pct_upper
WhiteTailedJackrabbit sc.fm2.1 D 102 9.641 3.40 78.16
WhiteTailedJackrabbit sc.fm2.1 snow 16500 0.713 0.28 1.24



notes:

moderate support for snow*temp, have a look,

snow is the top model, so mabey no interaction