广义估计方程分析结果中convergence not achieved是什么意思

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本人在用广义估计方程分析数据时，结果后面出现convergence not achieved，不懂是什么意思？还请各位指点迷津。我的数据类型是二分类，链接函数是logit，作业相关矩阵类型是unstructured。如果用独立或等相关的作业矩阵，就没有这样的结果出现，实在不懂为什么选择unstructured的矩阵类型是就会出现？

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关键词：Convergence converge achieved Achieve 广义估计方程 achieved

请问楼主的问题解决了吗，我也遇到类似的问题，还望楼主解答一下。convergence not achieved是什么意思，我是unbalanced data，固定效应

弥桑染冉 发表于 2016-5-30 12:57
请问楼主的问题解决了吗，我也遇到类似的问题，还望楼主解答一下。convergence not achieved是什么意思，我 ...

请问您的问题解决了嘛，是出现这是什么意思，出来的结果能不能用

看来大家都是一知半解，没人能回答。

popcornqing 发表于 2018-10-30 13:14
请问您的问题解决了嘛，是出现这是什么意思，出来的结果能不能用

考虑两个问题，也许能解决。
1、因变量分类是否恰当。
2、不同自变量标准差相差太远。
试试重新编码。
Here is my paraphrasing of an argument Scott Long has made concerning convergence problems:

Scaling of variables. Scaling can be important. The larger the ratio between the largest standard deviation and the smallest standard deviation, the more problems you will have with numerical methods. For example, if you have income measured in dollars, it may have a very large standard deviation relative to other variables. Recoding income to thousands of dollars may solve the problem. Long says that, in his experience, problems are much more likely when the ratio between the largest and smallest standard deviations exceeds 10. (You may want to rescale for presentation purposes anyway, e.g. the effect of 1 dollar of income may be extremely small and have to be reported to several decimal places; coding income in thousands of dollars
may make your tables look better.)