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我需要通过各个采样站计算粪便大肠菌群随时间的移动几何平均值（在每个值我想要该值的几何平均值和前 29 个值）。当我从我们的数据库下载数据时，列标题是：

Station SampleDate FecalColiform

根据种植面积的不同，有几个到十几个站。

我尝试修改在HERE找到的一些代码：

#File: Fecal
Fecal <- group_by(Fecal, Station) %>%
arrange(SampleDate) %>%
mutate(logres = log10(ResultValue)) %>%
mutate(mgm = stats::filter(logres, rep(1/24, 24), sides =1))

这行得通，但问题是我不想要生成的日志值。我只想要常规的 geomean，以便我可以绘制它并且每个人都可以轻松理解这些值。我试图以某种方式从其中的 psych 包中偷偷使用 geometry.mean 函数，但我无法完成这项工作。

有用于计算移动平均值的资源，以及用于计算几何平均值的代码，我尝试将其中的几个结合起来。我找不到移动几何平均值的示例。

最终，我想按类似于上面链接中的示例的站点来绘制所有几何平均值。

> dput(ByStationRGMData[1:10,])

structure(list(Station = c(114L, 114L, 114L, 114L, 114L, 114L, 
114L, 114L, 114L, 114L), Classification = structure(c(3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("  Approved  ", "  Conditionally        Approved  ", 
"  Prohibited  "), class = "factor"), SampleDate = c(19890103L, 
19890103L, 19890209L, 19890316L, 19890413L, 19890511L, 19890615L, 
19890713L, 19890817L, 19890914L), SWTemp = c(NA, NA, 5L, 8L, 
NA, 13L, 15L, 18L, NA, 18L), Salinity = c(NA, NA, 22L, 18L, NA, 
26L, 22L, 24L, NA, 32L), FecalColiform = c(180, 49, 2, 17, 7.9, 
1.8, 4.5, 11, 33, 1.8), RGM = c(NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
)), .Names = c("Station", "Classification", "SampleDate", "SWTemp", 
"Salinity", "FecalColiform", "RGM"), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -10L), vars = list(
Station), drop = TRUE, indices = list(0:9), group_sizes = 10L,      biggest_group_size = 10L, labels = structure(list(
Station = 114L), class = "data.frame", row.names = c(NA, 
-1L), vars = list(Station), drop = TRUE, .Names = "Station"))

我还想在数据框和图表中添加一个移动的 90%。我尝试了以下方法：

ByStationRGMData <- RawData %>%
group_by(Station) %>%
arrange(SampleDate) %>%
mutate(RGM = as.numeric(rollapply(FecalColiform, 30, geometric.mean,     fill=NA, align="right"))) +
mutate(F90 = as.numeric(rollapply(FecalColiform, 30, quantile, p=0.90, fill=NA, align="right")))

这给了我错误：

mutate_(.data, .dots = lazyeval::lazy_dots(...)) 中的错误：缺少参数“.data”，没有默认值

我似乎无法弄清楚我错过了什么。

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1 回答 1

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You can use rollapply from the zoo package (illustrated here using the built-in mtcars data frame). I've used a window of 3 values, but you can set that to 30 in your actual data. align="left" uses the current value and n-1 previous values, where n is the window width:

library(psych)
library(dplyr)
library(zoo)

mtcars %>% 
  mutate(mpgGM = rollapply(mpg, 3, geometric.mean, fill=NA, align="left"))

Include a grouping variable to get rolling geometric means separately for each group.

于 2015-11-24T21:37:17.867 回答