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 给泡妹（偶而冒个泡）的研究报告 |
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Nice try !!! -- 偶而冒个泡 - (685 Byte) 2009-10-10 周六, 05:38 (534 reads) |
乐闻德
[博客]
声望: 院士
性别:  年龄: 48
加入时间: 2009/08/02
文章: 6342
来自: Den Vereinigten Staaten
海归分: 47
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作者：乐闻德 在 海归茶馆 发贴, 来自【海归网】 http://www.haiguinet.com
I would also like to make some comments here:
(1) would you like to try fitting the data after making logarithm transformation? so that this nonlinear problem becomes linear, and could avoid using stepwise functions. (refer to Logistic Regression)
Not necessarily. EF is simply a mirror image of logarithm transformation. Just think in this way: should I use the natural logarithm to transform the dependent varialbe (real GDP per capita) and then run linear regression, it will still genearte the same function describled in the exponent part of my EFs.
(2) It seems to me you are pursuing an overfitting in your study, which could miss general underlying relationships. For instance, your discovery may work well only in China case, but not in other countries, say US case.
This may be a concern, but I don't worry too much about it. What I am interested are only the years positively/negatively deviated from the projected line, instead of trying to capture every observation under a single/multiple function(s).
(3) "70" comes from applying Taylor Series Expansion on (1+x)^n=2, where n denotes # of years, x denotes GDP growth rate. For even more details, please show me the money first.
I assume you consider a binomial series the best way to represent this relationship. Unfortunately, it may not be true under most circumstances. If you would like to know why, please donate more money to LeLe Foundation-every dollar counts!   
PS：你真不会用拼音啊？可怜的孩子~~~
作者：乐闻德 在 海归茶馆 发贴, 来自【海归网】 http://www.haiguinet.com
上一次由乐闻德于2009-10-11 周日, 00:09修改，总共修改了2次
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 给泡妹（偶而冒个泡）的研究报告 -- 乐闻德 - (945 Byte) 2009-10-09 周五, 00:13 (3643 reads) - 研究报告Part II -- 乐闻德 - (441 Byte) 2009-10-09 周五, 22:01 (582 reads)
- Nice try !!! -- 偶而冒个泡 - (685 Byte) 2009-10-10 周六, 05:38 (534 reads)
- Nice try too!!! -- 乐闻德 - (1598 Byte) 2009-10-10 周六, 08:31 (457 reads)
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