小鼠以很长的时间归纳 - 替代
我目前正在尝试弄清楚如何在面板数据中估算丢失值。我正在使用R和以下代码中的MICE
软件包:
miceIMP <- mice(dat, m = 10, maxit = 5, print=FALSE)
miceOutput <- complete(miceIMP)
我的数据是面板数据,该数据在数字数据列中缺少值( - &GT; Deal值)。其他列是因子变量,具有17级(年),38个级别(国家)和19个级别(行业)。数据有大约。因此,16,000行,这是一个较大的数据集。我已经试图将Maxit和M减少到1,但这似乎并没有改变任何东西。我也更改了插补方法,但是例如“ norm”,估算值变为负 - &gt;这是我的第二个问题,负值没有意义。这是我数据的屏幕截图。 数据示例
所以我的问题是:
- 您能告诉我如何减少运行时间(显着)并同时确保估算的值不会变成负面?
感谢您的帮助。
I'm currently trying to figure out how to impute missing values in my panel data. I'm using the mice
package in R and the following code:
miceIMP <- mice(dat, m = 10, maxit = 5, print=FALSE)
miceOutput <- complete(miceIMP)
My data is panel data which has missing values in a numeric data column (-> Deal Value). The other columns are factor variables with 17 levels (year), 38 levels (countries) and 19 levels (industries). The data has approx. 16,000 lines, hence, it's a larger data set. I already tried to reduce maxit and m to 1, but that didn't seem to change anything. I also changed the imputation methods, but with e.g. "norm" the imputed values become negative -> this is my second problem, negative values don't make sense. Here is a screenshot of my data.
Data Example
So my questions is:
- Can you tell me how I'm reducing the running time (significantly) and simultaneously ensure that the imputed values will not become negative?
Thank you for your help.
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