Research Article

Estimation for Weibull Parameters with Generalized Progressive Hybrid Censored Data

Table 1

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

MLENIP BayesIP Bayes

1100.319 2[0.212 3]0.205 1[0.086 1]0.285 8[0.163 5]0.197 1[0.079 5]0.237 5[0.104 4]0.131 3[0.028 4]
130.249 7[0.123 9]0.164 6[0.050 7]0.230 6[0.102 7]0.158 1[0.047 2]0.201 6[0.074 5]0.119 1[0.023 9]
2100.300 9[0.188 0]0.185 1[0.066 9]0.270 7[0.145 6]0.180 4[0.063 1]0.227 4[0.095 5]0.121 6[0.024 5]
130.260 3[0.135 2]0.170 3[0.060 8]0.239 9[0.111 5]0.165 8[0.057 9]0.209 8[0.080 7]0.121 0[0.024 9]
3150.232 6[0.102 3]0.148 4[0.042 8]0.216 7[0.087 1]0.144 1[0.040 6]0.194 7[0.067 9]0.112 5[0.021 8]
180.199 2[0.074 5]0.134 9[0.032 0]0.188 3[0.065 4]0.130 9[0.030 3]0.172 4[0.053 1]0.107 1[0.019 3]
4300.145 3[0.037 0]0.097 4[0.016 2]0.140 7[0.034 3]0.096 0[0.015 8]0.135 1[0.031 3]0.085 8[0.012 2]
350.132 5[0.029 8]0.091 4[0.013 9]0.128 9[0.027 9]0.090 0[0.013 5]0.123 9[0.025 6]0.081 5[0.010 9]
5300.137 1[0.032 0]0.099 6[0.016 5]0.133 3[0.030 8]0.097 8[0.016 0]0.127 4[0.027 2]0.086 9[0.012 4]
350.120 5[0.024 7]0.096 1[0.015 0]0.117 8[0.023 4]0.094 5[0.014 5]0.112 4[0.021 2]0.084 5[0.011 5]
6300.141 1[0.034 4]0.098 0[0.016 3]0.136 9[0.032 1]0.096 4[0.015 8]0.131 2[0.029 2]0.086 1[0.012 4]
350.124 7[0.026 2]0.092 5[0.013 8]0.121 5[0.024 7]0.091 1[0.013 4]0.116 5[0.022 5]0.082 1[0.010 8]

MLENIP BayesIP Bayes

1100.278 0[0.156 8]0.159 1[0.044 4]0.252 5[0.123 7]0.153 5[0.041 6]0.219 9[0.088 0]0.115 3[0.022 3]
130.246 5[0.119 3]0.161 3[0.045 8]0.227 4[0.099 1]0.154 7[0.042 6]0.198 6[0.072 1]0.117 9[0.023 2]
2100.242 0[0.111 8]0.154 1[0.047 4]0.225 1[0.093 5]0.151 9[0.045 7]0.202 9[0.072 8]0.116 6[0.023 4]
130.238 2[0.109 5]0.146 3[0.046 8]0.221 5[0.092 3]0.143 0[0.044 8]0.198 8[0.071 0]0.110 2[0.022 0]
3150.221 3[0.094 0]0.134 9[0.029 9]0.207 1[0.080 5]0.131 1[0.028 4]0.188 8[0.064 5]0.106 5[0.018 2]
180.196 5[0.071 9]0.131 6[0.029 3]0.185 9[0.063 2]0.127 7[0.027 7]0.170 0[0.051 5]0.105 1[0.018 2]
4300.144 9[0.036 5]0.092 5[0.013 8]0.140 2[0.033 8]0.091 2[0.013 4]0.134 8[0.031 0]0.082 0[0.010 8]
350.132 6[0.030 6]0.090 8[0.013 5]0.129 0[0.028 7]0.089 4[0.013 2]0.124 1[0.026 4]0.081 0[0.010 7]
5300.136 9[0.032 0]0.098 5[0.016 1]0.133 3[0.030 1]0.096 8[0.015 6]0.127 2[0.027 2]0.086 0[0.012 1]
350.119 6[0.024 1]0.095 9[0.014 7]0.116 8[0.022 8]0.094 3[0.014 3]0.111 3[0.020 5]0.084 3[0.011 3]
6300.143 1[0.035 3]0.097 2[0.015 7]0.138 7[0.032 8]0.095 6[0.015 2]0.132 8[0.029 8]0.085 5[0.012 0]
350.126 1[0.027 3]0.093 3[0.014 2]0.122 8[0.025 7]0.091 8[0.013 8]0.117 7[0.023 3]0.082 7[0.011 1]