试试：找到log likelihood 值不变的点，比如说是Iteration 100，然后在命令后加入  iterate(100)

。。。这个方法是不行。如果不converge就是不converge，通过限制iteration得到的“估计值”是不能用的。
可以换optimization algorithm，或者试试difficult option，或者换换initial value什么的。具体的去看help ml和help maximize

有的后面是not concave ,有的没有说明 ，有的是backed  up 是什么意思，下面这种情况如何处理？
Iteration 98:  log likelihood = -1770.2101  (not concave)
Iteration 99:  log likelihood = -1770.1672  
Iteration 100: log likelihood = -1770.0395  (not concave)
Iteration 101: log likelihood = -1769.9874  
Iteration 102: log likelihood = -1769.9096  
Iteration 103: log likelihood = -1769.8785  (not concave)
Iteration 104: log likelihood = -1769.8691  (not concave)
Iteration 105: log likelihood = -1769.8643  
Iteration 106: log likelihood =  -1769.864  (backed up)
Iteration 107: log likelihood = -1769.8638  (backed up)
Iteration 108: log likelihood = -1769.8637  (backed up)
Iteration 109: log likelihood = -1769.8627  
Iteration 110: log likelihood = -1769.8572  
Iteration 111: log likelihood = -1769.8504  (not concave)
Iteration 112: log likelihood = -1769.8492  
Iteration 113: log likelihood = -1769.8491  (backed up)
Iteration 114: log likelihood =  -1769.849  (not concave)
Iteration 115: log likelihood =  -1769.848  
Iteration 116: log likelihood = -1769.8476  (not concave)
Iteration 117: log likelihood = -1769.8476  
Iteration 118: log likelihood = -1769.8475  (not concave)
Iteration 119: log likelihood = -1769.8472  
Iteration 120: log likelihood =  -1769.847  (not concave)
Iteration 121: log likelihood =  -1769.847  
Iteration 122: log likelihood = -1769.8469  (not concave)
Iteration 123: log likelihood = -1769.8469  (not concave)
Iteration 124: log likelihood = -1769.8469  (not concave)
Iteration 125: log likelihood = -1769.8469  (not concave)
Iteration 126: log likelihood = -1769.8469  (not concave)
Iteration 127: log likelihood = -1769.8469  (not concave)
Iteration 128: log likelihood = -1769.8469  (not concave)
Iteration 129: log likelihood = -1769.8469  (not concave)
Iteration 130: log likelihood = -1769.8469  (not concave)
Iteration 131: log likelihood = -1769.8469  (not concave)
Iteration 132: log likelihood = -1769.8469  (not concave)
Iteration 133: log likelihood = -1769.8469  (not concave)
Iteration 134: log likelihood = -1769.8469  (not concave)
Iteration 135: log likelihood = -1769.8469  (not concave)
Iteration 136: log likelihood = -1769.8469  (not concave)
Iteration 137: log likelihood = -1769.8469  (not concave)
Iteration 138: log likelihood = -1769.8469  (not concave)
Iteration 139: log likelihood = -1769.8469  (not concave)
Iteration 140: log likelihood = -1769.8469  (not concave)
Iteration 141: log likelihood = -1769.8469  (not concave)
Iteration 142: log likelihood = -1769.8469  (not concave)
Iteration 143: log likelihood = -1769.8469  (not concave)
Iteration 144: log likelihood = -1769.8469  (not concave)
Iteration 145: log likelihood = -1769.8469  (not concave)
Iteration 146: log likelihood = -1769.8469  (not concave)
Iteration 147: log likelihood = -1769.8469  (not concave)
Iteration 148: log likelihood = -1769.8469  (not concave)
Iteration 149: log likelihood = -1769.8469  (not concave)
Iteration 150: log likelihood = -1769.8469  (not concave)
Iteration 151: log likelihood = -1769.8469  (not concave)
Iteration 152: log likelihood = -1769.8469  (not concave)
Iteration 153: log likelihood = -1769.8469  (not concave)
Iteration 154: log likelihood = -1769.8469  (not concave)
Iteration 155: log likelihood = -1769.8469  (not concave)
Iteration 156: log likelihood = -1769.8469  (not concave)
Iteration 157: log likelihood = -1769.8469  (not concave)
Iteration 158: log likelihood = -1769.8469  (not concave)
Iteration 159: log likelihood = -1769.8469  (not concave)
Iteration 160: log likelihood = -1769.8469  (not concave)
Iteration 161: log likelihood = -1769.8469  (not concave)
Iteration 162: log likelihood = -1769.8469  (not concave)
Iteration 163: log likelihood = -1769.8469  (not concave)
Iteration 164: log likelihood = -1769.8469  (not concave)
Iteration 165: log likelihood = -1769.8469  (not concave)
Iteration 166: log likelihood = -1769.8469  (not concave)
Iteration 167: log likelihood = -1769.8469  (not concave)
Iteration 168: log likelihood = -1769.8469  (not concave)
Iteration 169: log likelihood = -1769.8469  (not concave)
Iteration 170: log likelihood = -1769.8469  (not concave)
Iteration 171: log likelihood = -1769.8469  (not concave)
Iteration 172: log likelihood = -1769.8469  (not concave)
Iteration 173: log likelihood = -1769.8469  (not concave)
Iteration 174: log likelihood = -1769.8469  (not concave)
Iteration 175: log likelihood = -1769.8469  (not concave)
Iteration 176: log likelihood = -1769.8469  (not concave)
Iteration 177: log likelihood = -1769.8469  (not concave)
Iteration 178: log likelihood = -1769.8469  (not concave)
Iteration 179: log likelihood = -1769.8469  (not concave)
Iteration 180: log likelihood = -1769.8469  (not concave)
Iteration 181: log likelihood = -1769.8469  (not concave)
Iteration 182: log likelihood = -1769.8469  (not concave)
Iteration 183: log likelihood = -1769.8469  (not concave)
Iteration 184: log likelihood = -1769.8469  (not concave)
Iteration 185: log likelihood = -1769.8469  (not concave)
Iteration 186: log likelihood = -1769.8469  (not concave)
Iteration 187: log likelihood = -1769.8469  (not concave)
Iteration 188: log likelihood = -1769.8469  (not concave)
Iteration 189: log likelihood = -1769.8469  (not concave)
Iteration 190: log likelihood = -1769.8469  (not concave)
Iteration 191: log likelihood = -1769.8469  (not concave)
Iteration 192: log likelihood = -1769.8469  (not concave)
Iteration 193: log likelihood = -1769.8469  (not concave)
Iteration 194: log likelihood = -1769.8469  (not concave)
Iteration 195: log likelihood = -1769.84

没有的是好的。back up的也不行。

那我 如何处理呢  怎样能把movestay 命令完成 得到估计参数