求翻译:For each country we can write all aggregate variables in terms of是什么意思?待解决 悬赏分:1 - 离问题结束还有 For each country we can write all aggregate variables in terms of问题补充:匿名 2013-05-23 12:21:38 每个国家,我们可以写在所有聚合变量 匿名 2013-05-23 12:23:18 我...
上面的公式 cbind(mpg,hp) ~ cyl+gear 表示使用 cyl 和 gear 的因子组合对 cbind(mpg,hp) 数据进行操作。aggregate在时间序列数据上的应用请参考R的函数说明文档。 Example2 ## Compute the averages for the variables in 'state.x77', grouped
aggregate在时间序列数据上的应用请参考R的函数说明文档。 Example2 ## Compute the averages for the variables in 'state.x77', grouped ## according to the region (Northeast, South, North Central, West) that ## each state belongs to. aggregate(state.x77, list(Region = state.region), mean) #...
上面的公式 cbind(mpg,hp) ~ cyl+gear 表示使用 cyl 和 gear 的因子组合对 cbind(mpg,hp) 数据进行操作。aggregate在时间序列数据上的应用请参考R的函数说明文档。 Example2 ## Compute the averages for the variables in 'state.x77', grouped ## according to the region (Northeast, South, North Cent...
1980. Behavior of aggregate state variables in ecosystem models. Math. Biosci. 49: 121-137.Behavior of aggregate state variables in ecosystem models - Odell - 1980Cale, W.G., Jr. and Odell, P.L. 1980. Behavior of aggregate state variables in ecosystem models. Math. Biosci. 49: 121–...
R中aggregate函数的功能强大,它首先将数据进行分组(按行),然后对每一组数据进行函数统计,最后把结果组合成一个比较nice的表格返回。简单说有点类似sql语言中的group by,可以按照要求把数据打组聚合,然后对聚合以后的数据进行加和、求平均等各种操作。 2.详解 ...
Microeconometric Decompositions of Aggregate Variables: An Application to Labour Informality in Argentina - Gasparini - 2002Gasparini, L. C. (2002), "Microeconometric Decompositions of Aggregate Variables: An Application to Labour Informality in Argentina", Applied Economics, 34 (18): 2257-2266....
In R, I have changed the data to a star schema representation (when all metadata are represented row-wise and every value gets its own row) using reshape2 package and melt then used aggregate along different variables to get the different totals. The less variables you use in by the more...
aggregate在时间序列数据上的应用请参考R的函数说明文档。 Example2 ## Compute the averages for the variables in 'state.x77', grouped ## according to the region (Northeast, South, North Central, West) that ## each state belongs to. aggregate(state.x77, list(Region = state.region), mean) #...
In R, I have changed the data to a star schema representation (when all metadata are represented row-wise and every value gets its own row) using reshape2 package and melt then used aggregate along different variables to get the different totals. The less variables you use in by the more...