用平滑样条替换所有NA [英] Replacing all NAs with smoothing spline

问题描述

下面是样本数据(约8000行数据).如何用平滑样条拟合到其余数据的值替换所有NA?

Below is the sample data (out of approximately 8000 rows of data). How can I replace all NAs with values from a smoothing spline fit to the rest of the data?

Date            Max Min Rain    RHM RHE
4/24/1981   35.9    24.7    0.0 71  37
4/25/1981   36.8    22.8    0.0 62  40
4/26/1981   36.0    22.6    0.0 47  37
4/27/1981   35.1    24.2    0.0 51  39
4/28/1981   35.4    23.8    0.0 61  47
4/29/1981   35.4    25.1    0.0 67  43
4/30/1981   37.4    24.8    0.0 72  34
5/1/1981      NA      NA     NA NA  NA
5/2/1981    39.0    25.3     NA NA  55
5/3/1981    35.9    23.0    0.0 68  66
5/4/1981    28.4    22.4    0.7 70  30
5/5/1981    35.5    24.6    0.0 47  31
5/6/1981    37.4    25.5    0.0 51  31

推荐答案

我正在使用一些简化的数据来回答此查询.取得此数据集:

I'm using some simplified data for the purposes of answering this query. Take this dataset:

dat <- structure(list(x = c(1.6, 1.6, 4.4, 4.5, 6.1, 6.7, 7.3, 8, 9.5, 
9.5, 10.7), y = c(2.2, 4.5, 1.6, 4.3, NA, NA, 4.8, 7.3, 8.7, 6.3, 12.3)),
.Names = c("x", "y"), row.names = c(NA, -11L), class = "data.frame")

使用plot(dat,type="o",pch=19)绘制时的外观如下所示:

Which looks like the below when plotted using plot(dat,type="o",pch=19):

现在将平滑样条拟合到没有NA值的数据

Now fit a smoothing spline to the data without the NA values

smoo <- with(dat[!is.na(dat$y),],smooth.spline(x,y))

然后预测x的y值，其中y当前为NA

And then predict the y values for x, where y is currently NA

result <- with(dat,predict(smoo,x[is.na(y)]))
points(result,pch=19,col="red")

要将这些值重新填入原始数据，您可以执行以下操作:

To fill the values back into the original data you can then do:

dat[is.na(dat$y),] <- result

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