Year: 2019
Species: AmericanBlackBear
Study Site: Ritter Range
Metadata Summary:
| n_sites | N_detections | rep_period | model_agg_M | iterations | burnin | thin | state_buffer |
|---|---|---|---|---|---|---|---|
| 32 | 19 | 7 days | 300 | 350000 | 20000 | 20 | 2.5 |
WAIC
Models by WAIC:| model | description | WAIC |
|---|---|---|
| sc.fm4.2 | lure + snow + temp + pass | 164.2895 |
| sc.fm4.0 | lure + snow + temp | 164.4152 |
| sc.fm5.1 | lure + snow + temp + pass + lure * snow | 166.1720 |
| sc.fm5.0 | lure + snow + temp + pass + temp * snow | 166.5970 |
| sc.fm2.2 | temp | 170.1855 |
| sc.fm1 | dot model | 172.1906 |
| sc.fm2.0 | lure | 174.7588 |
| sc.fm2.1 | snow | 174.8586 |
| sc.fm3.0 | lure + snow | 176.1140 |
| sc.fm2.3 | pass | 176.4841 |
| sc.fm3.1 | lure + pass | 177.5892 |
Reversible Jump MCMC:
sc.fm6.0 model: (reverse jump) lure + snow + temp + pass + temp * snow + lure * snow| cov | indicator_mean |
|---|---|
| psi.ind | 0.12631 |
| beta.ind[3] | 0.00297 |
| beta.ind[1] | 0.00236 |
| beta.ind[2] | 0.00182 |
| beta.ind[4] | 0.00000 |
| beta.ind[5] | 0.00000 |
| beta.ind[6] | 0.00000 |
| cov | indicator_mean |
|---|---|
| psi.ind | 0.12630 |
| beta.ind[3] | 0.00455 |
| beta.ind[1] | 0.00194 |
| beta.ind[2] | 0.00194 |
| beta.ind[6] | 0.00164 |
| beta.ind[4] | 0.00109 |
| beta.ind[5] | 0.00073 |
| cov | indicator_mean |
|---|---|
| psi.ind | 0.16895 |
| beta.ind[3] | 0.00648 |
| beta.ind[1] | 0.00376 |
| beta.ind[2] | 0.00297 |
| beta.ind[4] | 0.00000 |
Model summaries:
sc.fm1 summary:
dot model
summary table
| param | n_effective | mean | mode | hdi_89pct_lower | hdi_89pct_upper | bayes_P |
|---|---|---|---|---|---|---|
| N | 11201 | 2.764 | 2.000 | 2.00 | 4.00 | 0 |
| D | 11201 | 1.552 | 1.123 | 1.12 | 2.25 | 0 |
| sigma | 14770 | 2.044 | 2.087 | 1.67 | 2.43 | 0 |
| lam0 | 13815 | 0.156 | 0.118 | 0.05 | 0.25 | 0 |
N
D
sigma
lam0
sc.fm2.0 summary:
lure
summary table
| param | n_effective | mean | mode | hdi_89pct_lower | hdi_89pct_upper | bayes_P |
|---|---|---|---|---|---|---|
| N | 9733 | 3.080 | 2.000 | 2.00 | 5.00 | 0.00000 |
| D | 9733 | 1.730 | 1.123 | 1.12 | 2.81 | 0.00000 |
| sigma | 13670 | 2.048 | 2.059 | 1.65 | 2.43 | 0.00000 |
| beta0.lam0 | 11184 | -2.301 | -2.214 | -3.13 | -1.49 | 0.00000 |
| beta.lam0[1] | 16500 | -0.567 | -0.513 | -1.11 | -0.03 | 0.24904 |
N
D
sigma
beta0.lam0
beta.lam0[1]
sc.fm2.1 summary:
snow
summary table
| param | n_effective | mean | mode | hdi_89pct_lower | hdi_89pct_upper | bayes_P |
|---|---|---|---|---|---|---|
| N | 6766 | 3.011 | 2.000 | 2.00 | 5.00 | 0.0000 |
| D | 6766 | 1.691 | 1.123 | 1.12 | 2.81 | 0.0000 |
| sigma | 14061 | 2.056 | 2.063 | 1.68 | 2.45 | 0.0000 |
| beta0.lam0 | 9862 | -2.232 | -2.113 | -3.02 | -1.39 | 0.0000 |
| beta.lam0[1] | 16904 | 0.405 | 0.413 | 0.05 | 0.78 | 0.1976 |
N
D
sigma
beta0.lam0
beta.lam0[1]
sc.fm2.2 summary:
temp
summary table
| param | n_effective | mean | mode | hdi_89pct_lower | hdi_89pct_upper | bayes_P |
|---|---|---|---|---|---|---|
| N | 6007 | 3.115 | 2.000 | 2.00 | 5.00 | 0.0000 |
| D | 6007 | 1.749 | 1.123 | 1.12 | 2.81 | 0.0000 |
| sigma | 13674 | 2.034 | 2.022 | 1.65 | 2.42 | 0.0000 |
| beta0.lam0 | 12066 | -2.339 | -2.222 | -3.12 | -1.56 | 0.0000 |
| beta.lam0[1] | 16008 | 0.505 | 0.518 | 0.11 | 0.91 | 0.1196 |
N
D
sigma
beta0.lam0
beta.lam0[1]
sc.fm2.3 summary:
pass
summary table
| param | n_effective | mean | mode | hdi_89pct_lower | hdi_89pct_upper | bayes_P |
|---|---|---|---|---|---|---|
| N | 10102 | 3.099 | 2.000 | 2.00 | 5.00 | 0.00000 |
| D | 10102 | 1.740 | 1.123 | 1.12 | 2.81 | 0.00000 |
| sigma | 13600 | 2.035 | 2.048 | 1.64 | 2.43 | 0.00000 |
| beta0.lam0 | 12814 | -2.160 | -2.123 | -2.95 | -1.34 | 0.00000 |
| beta.lam0[1] | 15764 | -0.014 | 0.027 | -0.90 | 0.88 | 0.99709 |
N
D
sigma
beta0.lam0
beta.lam0[1]
sc.fm3.0 summary:
lure + snow
summary table
| param | n_effective | mean | mode | hdi_89pct_lower | hdi_89pct_upper | bayes_P |
|---|---|---|---|---|---|---|
| N | 10282 | 2.968 | 2.000 | 2.00 | 5.00 | 0.00000 |
| D | 10282 | 1.667 | 1.123 | 1.12 | 2.81 | 0.00000 |
| sigma | 13712 | 2.065 | 2.089 | 1.67 | 2.45 | 0.00000 |
| beta0.lam0 | 10797 | -2.336 | -2.204 | -3.18 | -1.49 | 0.00000 |
| beta.lam0[1] | 16500 | -0.505 | -0.465 | -1.01 | 0.02 | 0.31806 |
| beta.lam0[2] | 16500 | 0.367 | 0.360 | 0.00 | 0.72 | 0.25711 |
N
D
sigma
beta0.lam0
beta.lam0[1]
beta.lam0[2]
sc.fm3.1 summary:
lure + pass
summary table
| param | n_effective | mean | mode | hdi_89pct_lower | hdi_89pct_upper | bayes_P |
|---|---|---|---|---|---|---|
| N | 9987 | 3.112 | 2.000 | 2.00 | 5.00 | 0.00000 |
| D | 9987 | 1.748 | 1.123 | 1.12 | 2.81 | 0.00000 |
| sigma | 14745 | 2.035 | 2.060 | 1.62 | 2.42 | 0.00000 |
| beta0.lam0 | 12213 | -2.288 | -2.243 | -3.10 | -1.41 | 0.00000 |
| beta.lam0[1] | 16933 | -0.563 | -0.472 | -1.06 | 0.00 | 0.27194 |
| beta.lam0[2] | 15953 | -0.073 | -0.080 | -0.96 | 0.82 | 0.99293 |
N
D
sigma
beta0.lam0
beta.lam0[1]
beta.lam0[2]
sc.fm4.0 summary:
lure + snow + temp
summary table
| param | n_effective | mean | mode | hdi_89pct_lower | hdi_89pct_upper | bayes_P |
|---|---|---|---|---|---|---|
| N | 10218 | 2.876 | 2.000 | 2.00 | 4.00 | 0.00000 |
| D | 10218 | 1.615 | 1.123 | 1.12 | 2.25 | 0.00000 |
| sigma | 14020 | 2.035 | 2.056 | 1.66 | 2.40 | 0.00000 |
| beta0.lam0 | 12248 | -2.824 | -2.754 | -3.75 | -1.89 | 0.00000 |
| beta.lam0[1] | 16647 | -0.850 | -0.716 | -1.49 | -0.18 | 0.08283 |
| beta.lam0[2] | 16500 | 0.625 | 0.618 | 0.23 | 1.03 | 0.04719 |
| beta.lam0[3] | 16500 | 1.210 | 1.209 | 0.59 | 1.84 | 0.00291 |
N
D
sigma
beta0.lam0
beta.lam0[1]
beta.lam0[2]
beta.lam0[3]
sc.fm4.2 summary:
lure + snow + temp + pass
summary table
| param | n_effective | mean | mode | hdi_89pct_lower | hdi_89pct_upper | bayes_P |
|---|---|---|---|---|---|---|
| N | 11527 | 3.118 | 2.997 | 2.00 | 4.00 | 0.00000 |
| D | 11527 | 1.751 | 1.683 | 1.12 | 2.25 | 0.00000 |
| sigma | 14156 | 1.985 | 1.986 | 1.61 | 2.36 | 0.00000 |
| beta0.lam0 | 14207 | -2.617 | -2.536 | -3.54 | -1.70 | 0.00000 |
| beta.lam0[1] | 16500 | -0.838 | -0.765 | -1.43 | -0.20 | 0.06244 |
| beta.lam0[2] | 16136 | 0.714 | 0.699 | 0.28 | 1.11 | 0.02103 |
| beta.lam0[3] | 17076 | 1.268 | 1.190 | 0.62 | 1.87 | 0.00248 |
| beta.lam0[4] | 16104 | -0.730 | -0.602 | -1.67 | 0.18 | 0.47343 |
N
D
sigma
beta0.lam0
beta.lam0[1]
beta.lam0[2]
beta.lam0[3]
beta.lam0[4]
sc.fm5.0 summary:
lure + snow + temp + pass + temp * snow
summary table
| param | n_effective | mean | mode | hdi_89pct_lower | hdi_89pct_upper | bayes_P |
|---|---|---|---|---|---|---|
| N | 12192 | 3.127 | 2.000 | 2.00 | 4.00 | 0.00000 |
| D | 12192 | 1.756 | 1.123 | 1.12 | 2.25 | 0.00000 |
| sigma | 14919 | 1.985 | 2.008 | 1.61 | 2.37 | 0.00000 |
| beta0.lam0 | 14403 | -2.620 | -2.607 | -3.53 | -1.66 | 0.00000 |
| beta.lam0[1] | 16931 | -0.820 | -0.695 | -1.43 | -0.19 | 0.08331 |
| beta.lam0[2] | 16897 | 0.664 | 0.607 | 0.19 | 1.14 | 0.07285 |
| beta.lam0[3] | 14180 | 1.264 | 1.258 | 0.62 | 1.88 | 0.00406 |
| beta.lam0[4] | 15756 | -0.702 | -0.667 | -1.65 | 0.22 | 0.51039 |
| beta.lam0[5] | 16500 | 0.131 | 0.103 | -0.43 | 0.70 | 0.93501 |
N
D
sigma
beta0.lam0
beta.lam0[1]
beta.lam0[2]
beta.lam0[3]
beta.lam0[4]
beta.lam0[5]
sc.fm5.1 summary:
lure + snow + temp + pass + lure * snow
summary table
| param | n_effective | mean | mode | hdi_89pct_lower | hdi_89pct_upper | bayes_P |
|---|---|---|---|---|---|---|
| N | 11594 | 3.122 | 3.017 | 2.00 | 4.00 | 0.00000 |
| D | 11594 | 1.753 | 1.694 | 1.12 | 2.25 | 0.00000 |
| sigma | 14479 | 1.984 | 1.992 | 1.61 | 2.35 | 0.00000 |
| beta0.lam0 | 14182 | -2.726 | -2.628 | -3.67 | -1.76 | 0.00000 |
| beta.lam0[1] | 16500 | -0.949 | -0.869 | -1.58 | -0.28 | 0.04020 |
| beta.lam0[2] | 17706 | 0.565 | 0.567 | -0.01 | 1.13 | 0.27191 |
| beta.lam0[3] | 16500 | 1.256 | 1.184 | 0.61 | 1.90 | 0.00461 |
| beta.lam0[4] | 15853 | -0.705 | -0.670 | -1.62 | 0.23 | 0.49187 |
| beta.lam0[5] | 16500 | -0.215 | -0.179 | -0.79 | 0.39 | 0.88691 |
N
D
sigma
beta0.lam0
beta.lam0[1]
beta.lam0[2]
beta.lam0[3]
beta.lam0[4]
beta.lam0[5]
