Calculates posterior inclusion probabilities (PIPs) for modifiers in HDLM & HDLMM
Source:R/pip.R
pip.RdMethod for calculating posterior inclusion probabilities (PIPs) for modifiers in HDLM & HDLMM
Value
numeric vector of PIPs named with modifiers (type=1) or data.frame of PIPs with the following columns (type=2):
- var1
first modifier of joint modifiers
- var2
second modifier of joint modifiers
- pip
joint PIPs for the two modifiers
Examples
# \donttest{
# Posterior inclusion probability with HDLM
D <- sim.hdlmm(sim = "B", n = 1000)
fit <- dlmtree(y ~ .,
data = D$dat,
exposure.data = D$exposures,
dlm.type = "linear",
family = "gaussian",
het = TRUE)
#> Preparing data...
#>
#> Running shared HDLM:
#> Burn-in % complete
#> [0--------25--------50--------75--------100]
#> ''''''''''''''''''''''''''''''''''''''''''
#> MCMC iterations (est time: 6 seconds)
#> [0--------25--------50--------75--------100]
#> ''''''''''''''''''''''''''''''''''''''''''
#> Compiling results...
pip(fit)
#> mod_num mod_bin mod_scale c1 c2 c3 c4 c5
#> 1.000 0.295 1.000 0.360 0.350 0.375 0.435 0.395
#> b1 b2 b3 b4 b5
#> 0.320 0.300 0.300 0.330 0.315
pip(fit, type = 2)
#> var1 var2 pip
#> 3 mod_num mod_scale 1.000
#> 27 mod_scale mod_num 1.000
#> 29 mod_scale mod_scale 0.635
#> 1 mod_num mod_num 0.430
#> 33 mod_scale c4 0.225
#> 81 c4 mod_scale 0.225
#> 34 mod_scale c5 0.175
#> 94 c5 mod_scale 0.175
#> 7 mod_num c4 0.165
#> 79 c4 mod_num 0.165
#> 6 mod_num c3 0.150
#> 66 c3 mod_num 0.150
#> 32 mod_scale c3 0.145
#> 68 c3 mod_scale 0.145
#> 10 mod_num b2 0.140
#> 31 mod_scale c2 0.140
#> 55 c2 mod_scale 0.140
#> 118 b2 mod_num 0.140
#> 8 mod_num c5 0.125
#> 36 mod_scale b2 0.125
#> 92 c5 mod_num 0.125
#> 120 b2 mod_scale 0.125
#> 30 mod_scale c1 0.120
#> 39 mod_scale b5 0.120
#> 42 c1 mod_scale 0.120
#> 159 b5 mod_scale 0.120
#> 37 mod_scale b3 0.115
#> 133 b3 mod_scale 0.115
#> 5 mod_num c2 0.110
#> 11 mod_num b3 0.110
#> 53 c2 mod_num 0.110
#> 131 b3 mod_num 0.110
#> 2 mod_num mod_bin 0.100
#> 9 mod_num b1 0.100
#> 14 mod_bin mod_num 0.100
#> 35 mod_scale b1 0.100
#> 105 b1 mod_num 0.100
#> 107 b1 mod_scale 0.100
#> 38 mod_scale b4 0.085
#> 146 b4 mod_scale 0.085
#> 4 mod_num c1 0.075
#> 16 mod_bin mod_scale 0.075
#> 28 mod_scale mod_bin 0.075
#> 40 c1 mod_num 0.075
#> 12 mod_num b4 0.070
#> 144 b4 mod_num 0.070
#> 85 c4 c4 0.065
#> 13 mod_num b5 0.060
#> 59 c2 c4 0.060
#> 83 c4 c2 0.060
#> 157 b5 mod_num 0.060
#> 91 c4 b5 0.055
#> 163 b5 c4 0.055
#> 20 mod_bin c4 0.045
#> 43 c1 c1 0.045
#> 46 c1 c4 0.045
#> 57 c2 c2 0.045
#> 58 c2 c3 0.045
#> 62 c2 b2 0.045
#> 64 c2 b4 0.045
#> 70 c3 c2 0.045
#> 71 c3 c3 0.045
#> 75 c3 b2 0.045
#> 80 c4 mod_bin 0.045
#> 82 c4 c1 0.045
#> 122 b2 c2 0.045
#> 123 b2 c3 0.045
#> 148 b4 c2 0.045
#> 156 b4 b5 0.045
#> 168 b5 b4 0.045
#> 17 mod_bin c1 0.040
#> 18 mod_bin c2 0.040
#> 19 mod_bin c3 0.040
#> 26 mod_bin b5 0.040
#> 41 c1 mod_bin 0.040
#> 54 c2 mod_bin 0.040
#> 67 c3 mod_bin 0.040
#> 77 c3 b4 0.040
#> 90 c4 b4 0.040
#> 99 c5 c5 0.040
#> 104 c5 b5 0.040
#> 149 b4 c3 0.040
#> 150 b4 c4 0.040
#> 158 b5 mod_bin 0.040
#> 164 b5 c5 0.040
#> 52 c1 b5 0.035
#> 63 c2 b3 0.035
#> 65 c2 b5 0.035
#> 76 c3 b3 0.035
#> 117 b1 b5 0.035
#> 129 b2 b4 0.035
#> 135 b3 c2 0.035
#> 136 b3 c3 0.035
#> 153 b4 b2 0.035
#> 160 b5 c1 0.035
#> 161 b5 c2 0.035
#> 165 b5 b1 0.035
#> 21 mod_bin c5 0.030
#> 50 c1 b3 0.030
#> 72 c3 c4 0.030
#> 84 c4 c3 0.030
#> 86 c4 c5 0.030
#> 87 c4 b1 0.030
#> 88 c4 b2 0.030
#> 93 c5 mod_bin 0.030
#> 98 c5 c4 0.030
#> 111 b1 c4 0.030
#> 124 b2 c4 0.030
#> 130 b2 b5 0.030
#> 134 b3 c1 0.030
#> 166 b5 b2 0.030
#> 25 mod_bin b4 0.025
#> 44 c1 c2 0.025
#> 48 c1 b1 0.025
#> 49 c1 b2 0.025
#> 56 c2 c1 0.025
#> 73 c3 c5 0.025
#> 97 c5 c3 0.025
#> 102 c5 b3 0.025
#> 103 c5 b4 0.025
#> 108 b1 c1 0.025
#> 121 b2 c1 0.025
#> 138 b3 c5 0.025
#> 145 b4 mod_bin 0.025
#> 151 b4 c5 0.025
#> 47 c1 c5 0.020
#> 51 c1 b4 0.020
#> 60 c2 c5 0.020
#> 74 c3 b1 0.020
#> 89 c4 b3 0.020
#> 95 c5 c1 0.020
#> 96 c5 c2 0.020
#> 100 c5 b1 0.020
#> 110 b1 c3 0.020
#> 112 b1 c5 0.020
#> 128 b2 b3 0.020
#> 137 b3 c4 0.020
#> 140 b3 b2 0.020
#> 143 b3 b5 0.020
#> 147 b4 c1 0.020
#> 167 b5 b3 0.020
#> 22 mod_bin b1 0.015
#> 24 mod_bin b3 0.015
#> 61 c2 b1 0.015
#> 78 c3 b5 0.015
#> 101 c5 b2 0.015
#> 106 b1 mod_bin 0.015
#> 109 b1 c2 0.015
#> 125 b2 c5 0.015
#> 132 b3 mod_bin 0.015
#> 142 b3 b4 0.015
#> 154 b4 b3 0.015
#> 162 b5 c3 0.015
#> 45 c1 c3 0.010
#> 69 c3 c1 0.010
#> 115 b1 b3 0.010
#> 139 b3 b1 0.010
#> 23 mod_bin b2 0.005
#> 114 b1 b2 0.005
#> 116 b1 b4 0.005
#> 119 b2 mod_bin 0.005
#> 126 b2 b1 0.005
#> 152 b4 b1 0.005
#> 15 mod_bin mod_bin 0.000
#> 113 b1 b1 0.000
#> 127 b2 b2 0.000
#> 141 b3 b3 0.000
#> 155 b4 b4 0.000
#> 169 b5 b5 0.000
# }