Research Article

Estimation for Weibull Parameters with Generalized Progressive Hybrid Censored Data

Table 3

ABs and MSEs (within brackets) of the MLEs and Bayes estimates under generalized progressively hybrid censored data with .

MLENIP BayesIP Bayes

1100.496 3[0.512 5]0.563 6[0.631 8]0.414 6[0.335 3]0.528 9[0.573 6]0.286 2[0.138 6]0.296 0[0.170 9]
130.383 4[0.286 1]0.307 0[0.285 9]0.337 3[0.212 6]0.292 1[0.260 5]0.267 7[0.123 3]0.241 0[0.114 4]
2100.487 5[0.495 7]0.651 7[0.755 4]0.405 6[0.320 2]0.602 3[0.581 7]0.263 9[0.115 8]0.303 1[0.167 3]
130.395 7[0.311 4]0.390 0[0.573 5]0.345 9[0.227 1]0.374 2[0.526 8]0.260 8[0.116 4]0.262 1[0.134 1]
3150.347 2[0.235 2]0.297 6[0.232 9]0.309 9[0.180 6]0.285 7[0.211 1]0.249 4[0.108 0]0.233 0[0.105 6]
180.295 1[0.162 3]0.229 5[0.115 1]0.271 1[0.132 4]0.221 9[0.106 7]0.231 9[0.092 5]0.199 9[0.076 2]
4300.219 5[0.083 5]0.179 0[0.064 7]0.208 2[0.073 7]0.175 7[0.061 9]0.188 7[0.059 3]0.163 6[0.050 2]
350.197 8[0.067 1]0.151 2[0.040 9]0.189 1[0.060 4]0.148 7[0.039 4]0.175 3[0.051 2]0.142 6[0.035 4]
5300.202 8[0.069 6]0.163 9[0.048 8]0.193 8[0.062 6]0.160 8[0.046 7]0.178 9[0.052 6]0.153 6[0.041 5]
350.181 4[0.055 5]0.144 0[0.035 2]0.175 1[0.050 9]0.141 5[0.033 9]0.164 3[0.044 4]0.136 8[0.031 5]
6300.211 1[0.076 6]0.168 3[0.054 0]0.200 9[0.068 3]0.165 2[0.051 7]0.183 5[0.056 0]0.156 2[0.044 1]
350.190 4[0.062 3]0.149 1[0.039 0]0.183 1[0.056 6]0.146 5[0.037 5]0.170 7[0.048 6]0.141 3[0.034 3]

MLENIP BayesIP Bayes

1100.388 4[0.295 6]0.269 8[0.156 3]0.338 0[0.209 9]0.259 1[0.140 6]0.262 6[0.115 8]0.223 4[0.092 1]
130.359 0[0.247 4]0.275 3[0.156 0]0.318 1[0.186 1]0.262 2[0.140 6]0.257 0[0.113 3]0.229 3[0.095 4]
2100.351 7[0.237 6]0.320 5[0.273 7]0.316 0[0.182 5]0.311 4[0.250 9]0.251 0[0.106 1]0.253 2[0.117 7]
130.357 7[0.242 0]0.315 4[0.285 2]0.319 8[0.185 2]0.305 7[0.260 6]0.254 4[0.108 7]0.247 1[0.114 9]
3150.312 5[0.181 1]0.224 7[0.096 1]0.284 3[0.143 8]0.217 1[0.089 4]0.238 1[0.096 0]0.195 9[0.068 9]
180.288 1[0.151 3]0.224 7[0.097 6]0.263 9[0.123 5]0.217 0[0.090 4]0.227 0[0.087 8]0.198 3[0.070 6]
4300.209 9[0.076 2]0.150 4[0.038 0]0.200 2[0.068 0]0.147 9[0.036 7]0.183 6[0.056 3]0.141 3[0.033 1]
350.196 2[0.065 4]0.147 2[0.037 4]0.187 7[0.058 9]0.144 6[0.036 0]0.174 1[0.050 1]0.139 0[0.032 8]
5300.204 4[0.072 4]0.162 4[0.047 4]0.194 7[0.064 8]0.159 3[0.045 4]0.179 9[0.054 5]0.152 2[0.040 6]
350.179 5[0.054 7]0.146 8[0.037 5]0.172 9[0.050 1]0.144 2[0.036 1]0.162 4[0.043 8]0.139 2[0.033 4]
6300.209 7[0.075 8]0.163 1[0.045 2]0.200 0[0.067 7]0.160 1[0.043 3]0.183 5[0.056 1]0.152 6[0.038 8]
350.189 9[0.060 8]0.146 6[0.037 7]0.182 5[0.055 3]0.144 0[0.036 2]0.170 4[0.047 6]0.138 9[0.033 2]