|
4 | 4 | report(model, verbose = FALSE) |
5 | 5 | Message |
6 | 6 | Start sampling |
| 7 | + Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue: |
| 8 | + Chain 1 Exception: normal_id_glm_lpdf: Scale vector is 0, but must be positive finite! (in 'C:/Users/DL/AppData/Local/Temp/RtmpERRA9z/model-12d437f47a61.stan', line 35, column 4 to column 62) |
| 9 | + Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine, |
| 10 | + Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified. |
| 11 | + Chain 1 |
| 12 | + Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue: |
| 13 | + Chain 2 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in 'C:/Users/DL/AppData/Local/Temp/RtmpERRA9z/model-12d437f47a61.stan', line 35, column 4 to column 62) |
| 14 | + Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine, |
| 15 | + Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified. |
| 16 | + Chain 2 |
| 17 | + Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue: |
| 18 | + Chain 2 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in 'C:/Users/DL/AppData/Local/Temp/RtmpERRA9z/model-12d437f47a61.stan', line 35, column 4 to column 62) |
| 19 | + Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine, |
| 20 | + Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified. |
| 21 | + Chain 2 |
| 22 | + Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue: |
| 23 | + Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in 'C:/Users/DL/AppData/Local/Temp/RtmpERRA9z/model-12d437f47a61.stan', line 35, column 4 to column 62) |
| 24 | + Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine, |
| 25 | + Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified. |
| 26 | + Chain 3 |
| 27 | + Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue: |
| 28 | + Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in 'C:/Users/DL/AppData/Local/Temp/RtmpERRA9z/model-12d437f47a61.stan', line 35, column 4 to column 62) |
| 29 | + Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine, |
| 30 | + Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified. |
| 31 | + Chain 3 |
| 32 | + Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue: |
| 33 | + Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in 'C:/Users/DL/AppData/Local/Temp/RtmpERRA9z/model-12d437f47a61.stan', line 35, column 4 to column 62) |
| 34 | + Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine, |
| 35 | + Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified. |
| 36 | + Chain 3 |
| 37 | + Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue: |
| 38 | + Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in 'C:/Users/DL/AppData/Local/Temp/RtmpERRA9z/model-12d437f47a61.stan', line 35, column 4 to column 62) |
| 39 | + Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine, |
| 40 | + Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified. |
| 41 | + Chain 3 |
7 | 42 | Output |
8 | 43 | We fitted a Bayesian linear model (estimated using MCMC sampling with 4 chains |
9 | 44 | of 300 iterations and a warmup of 150) to predict mpg with qsec and wt |
|
12 | 47 | is substantial (R2 = 0.82, 95% CI [0.75, 0.85], adj. R2 = 0.79). Within this |
13 | 48 | model: |
14 | 49 | |
15 | | - - The effect of b Intercept (Median = 19.74, 95% CI [9.45, 32.02]) has a 99.83% |
16 | | - probability of being positive (> 0), 99.83% of being significant (> 0.30), and |
17 | | - 99.67% of being large (> 1.81). The estimation successfully converged (Rhat = |
18 | | - 1.000) but the indices are unreliable (ESS = 522) |
19 | | - - The effect of b qsec (Median = 0.92, 95% CI [0.34, 1.47]) has a 99.83% |
20 | | - probability of being positive (> 0), 98.17% of being significant (> 0.30), and |
21 | | - 0.17% of being large (> 1.81). The estimation successfully converged (Rhat = |
22 | | - 1.002) but the indices are unreliable (ESS = 521) |
23 | | - - The effect of b wt (Median = -5.09, 95% CI [-6.06, -4.09]) has a 100.00% |
| 50 | + - The effect of b Intercept (Median = 19.23, 95% CI [6.80, 31.02]) has a 99.67% |
| 51 | + probability of being positive (> 0), 99.67% of being significant (> 0.30), and |
| 52 | + 99.33% of being large (> 1.81). The estimation successfully converged (Rhat = |
| 53 | + 0.999) but the indices are unreliable (ESS = 343) |
| 54 | + - The effect of b qsec (Median = 0.95, 95% CI [0.41, 1.56]) has a 100.00% |
| 55 | + probability of being positive (> 0), 99.17% of being significant (> 0.30), and |
| 56 | + 0.33% of being large (> 1.81). The estimation successfully converged (Rhat = |
| 57 | + 0.999) but the indices are unreliable (ESS = 345) |
| 58 | + - The effect of b wt (Median = -5.02, 95% CI [-6.06, -4.09]) has a 100.00% |
24 | 59 | probability of being negative (< 0), 100.00% of being significant (< -0.30), |
25 | 60 | and 100.00% of being large (< -1.81). The estimation successfully converged |
26 | | - (Rhat = 0.997) but the indices are unreliable (ESS = 543) |
| 61 | + (Rhat = 0.999) but the indices are unreliable (ESS = 586) |
27 | 62 | |
28 | 63 | Following the Sequential Effect eXistence and sIgnificance Testing (SEXIT) |
29 | 64 | framework, we report the median of the posterior distribution and its 95% CI |
|
41 | 76 | substantial (R2 = 0.82, 95% CI [0.75, 0.85], adj. R2 = 0.79). Within this |
42 | 77 | model: |
43 | 78 | |
44 | | - - The effect of b Intercept (Median = 19.74, 95% CI [9.45, 32.02]) has a 99.83% |
45 | | - probability of being positive (> 0), 99.83% of being significant (> 0.30), and |
46 | | - 99.67% of being large (> 1.81). The estimation successfully converged (Rhat = |
47 | | - 1.000) but the indices are unreliable (ESS = 522) |
48 | | - - The effect of b qsec (Median = 0.92, 95% CI [0.34, 1.47]) has a 99.83% |
49 | | - probability of being positive (> 0), 98.17% of being significant (> 0.30), and |
50 | | - 0.17% of being large (> 1.81). The estimation successfully converged (Rhat = |
51 | | - 1.002) but the indices are unreliable (ESS = 521) |
52 | | - - The effect of b wt (Median = -5.09, 95% CI [-6.06, -4.09]) has a 100.00% |
| 79 | + - The effect of b Intercept (Median = 19.23, 95% CI [6.80, 31.02]) has a 99.67% |
| 80 | + probability of being positive (> 0), 99.67% of being significant (> 0.30), and |
| 81 | + 99.33% of being large (> 1.81). The estimation successfully converged (Rhat = |
| 82 | + 0.999) but the indices are unreliable (ESS = 343) |
| 83 | + - The effect of b qsec (Median = 0.95, 95% CI [0.41, 1.56]) has a 100.00% |
| 84 | + probability of being positive (> 0), 99.17% of being significant (> 0.30), and |
| 85 | + 0.33% of being large (> 1.81). The estimation successfully converged (Rhat = |
| 86 | + 0.999) but the indices are unreliable (ESS = 345) |
| 87 | + - The effect of b wt (Median = -5.02, 95% CI [-6.06, -4.09]) has a 100.00% |
53 | 88 | probability of being negative (< 0), 100.00% of being significant (< -0.30), |
54 | 89 | and 100.00% of being large (< -1.81). The estimation successfully converged |
55 | | - (Rhat = 0.997) but the indices are unreliable (ESS = 543) |
| 90 | + (Rhat = 0.999) but the indices are unreliable (ESS = 586) |
56 | 91 | |
57 | 92 | Following the Sequential Effect eXistence and sIgnificance Testing (SEXIT) |
58 | 93 | framework, we report the median of the posterior distribution and its 95% CI |
|
70 | 105 | substantial (R2 = 0.82, 95% CI [0.75, 0.85], adj. R2 = 0.79). Within this |
71 | 106 | model: |
72 | 107 | |
73 | | - - The effect of b Intercept (Median = 19.74, 95% CI [9.45, 32.02]) has a 99.83% |
74 | | - probability of being positive (> 0), 99.83% of being significant (> 0.30), and |
75 | | - 99.67% of being large (> 1.81). The estimation successfully converged (Rhat = |
76 | | - 1.000) but the indices are unreliable (ESS = 522) |
77 | | - - The effect of b qsec (Median = 0.92, 95% CI [0.34, 1.47]) has a 99.83% |
78 | | - probability of being positive (> 0), 98.17% of being significant (> 0.30), and |
79 | | - 0.17% of being large (> 1.81). The estimation successfully converged (Rhat = |
80 | | - 1.002) but the indices are unreliable (ESS = 521) |
81 | | - - The effect of b wt (Median = -5.09, 95% CI [-6.06, -4.09]) has a 100.00% |
| 108 | + - The effect of b Intercept (Median = 19.23, 95% CI [6.80, 31.02]) has a 99.67% |
| 109 | + probability of being positive (> 0), 99.67% of being significant (> 0.30), and |
| 110 | + 99.33% of being large (> 1.81). The estimation successfully converged (Rhat = |
| 111 | + 0.999) but the indices are unreliable (ESS = 343) |
| 112 | + - The effect of b qsec (Median = 0.95, 95% CI [0.41, 1.56]) has a 100.00% |
| 113 | + probability of being positive (> 0), 99.17% of being significant (> 0.30), and |
| 114 | + 0.33% of being large (> 1.81). The estimation successfully converged (Rhat = |
| 115 | + 0.999) but the indices are unreliable (ESS = 345) |
| 116 | + - The effect of b wt (Median = -5.02, 95% CI [-6.06, -4.09]) has a 100.00% |
82 | 117 | probability of being negative (< 0), 100.00% of being significant (< -0.30), |
83 | 118 | and 100.00% of being large (< -1.81). The estimation successfully converged |
84 | | - (Rhat = 0.997) but the indices are unreliable (ESS = 543) |
| 119 | + (Rhat = 0.999) but the indices are unreliable (ESS = 586) |
85 | 120 | |
86 | 121 | Following the Sequential Effect eXistence and sIgnificance Testing (SEXIT) |
87 | 122 | framework, we report the median of the posterior distribution and its 95% CI |
|
99 | 134 | substantial (R2 = 0.82, 95% CI [0.75, 0.85], adj. R2 = 0.79). Within this |
100 | 135 | model: |
101 | 136 | |
102 | | - - The effect of b Intercept (Median = 19.74, 95% CI [9.45, 32.02]) has a 99.83% |
103 | | - probability of being positive (> 0), 99.83% of being significant (> 0.30), and |
104 | | - 99.67% of being large (> 1.81). The estimation successfully converged (Rhat = |
105 | | - 1.000) but the indices are unreliable (ESS = 522) |
106 | | - - The effect of b qsec (Median = 0.92, 95% CI [0.34, 1.47]) has a 99.83% |
107 | | - probability of being positive (> 0), 98.17% of being significant (> 0.30), and |
108 | | - 0.17% of being large (> 1.81). The estimation successfully converged (Rhat = |
109 | | - 1.002) but the indices are unreliable (ESS = 521) |
110 | | - - The effect of b wt (Median = -5.09, 95% CI [-6.06, -4.09]) has a 100.00% |
| 137 | + - The effect of b Intercept (Median = 19.23, 95% CI [6.80, 31.02]) has a 99.67% |
| 138 | + probability of being positive (> 0), 99.67% of being significant (> 0.30), and |
| 139 | + 99.33% of being large (> 1.81). The estimation successfully converged (Rhat = |
| 140 | + 0.999) but the indices are unreliable (ESS = 343) |
| 141 | + - The effect of b qsec (Median = 0.95, 95% CI [0.41, 1.56]) has a 100.00% |
| 142 | + probability of being positive (> 0), 99.17% of being significant (> 0.30), and |
| 143 | + 0.33% of being large (> 1.81). The estimation successfully converged (Rhat = |
| 144 | + 0.999) but the indices are unreliable (ESS = 345) |
| 145 | + - The effect of b wt (Median = -5.02, 95% CI [-6.06, -4.09]) has a 100.00% |
111 | 146 | probability of being negative (< 0), 100.00% of being significant (< -0.30), |
112 | 147 | and 100.00% of being large (< -1.81). The estimation successfully converged |
113 | | - (Rhat = 0.997) but the indices are unreliable (ESS = 543) |
| 148 | + (Rhat = 0.999) but the indices are unreliable (ESS = 586) |
114 | 149 | |
115 | 150 | Following the Sequential Effect eXistence and sIgnificance Testing (SEXIT) |
116 | 151 | framework, we report the median of the posterior distribution and its 95% CI |
|
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