Warning: file_get_contents(/data/phpspider/zhask/data//catemap/4/r/70.json): failed to open stream: No such file or directory in /data/phpspider/zhask/libs/function.php on line 167

Warning: Invalid argument supplied for foreach() in /data/phpspider/zhask/libs/tag.function.php on line 1116

Notice: Undefined index: in /data/phpspider/zhask/libs/function.php on line 180

Warning: array_chunk() expects parameter 1 to be array, null given in /data/phpspider/zhask/libs/function.php on line 181
R 用不同的插值技术在时序数据中填充NA_R_Interpolation_Na - Fatal编程技术网

R 用不同的插值技术在时序数据中填充NA

R 用不同的插值技术在时序数据中填充NA,r,interpolation,na,R,Interpolation,Na,我有四列(1个时间数据,3个连续数据)。我在每列中都有许多NA值。我想为所有列插入和填充NA。因为我不知道我需要哪种插值方法,所以我想要很多插值方法(线性、样条等)。我试过na.Abrox,但没用 有什么帮助吗?df如果您想尝试并比较上述几种插值方法,您可以使用

我有四列(1个时间数据,3个连续数据)。我在每列中都有许多NA值。我想为所有列插入和填充NA。因为我不知道我需要哪种插值方法,所以我想要很多插值方法(线性、样条等)。我试过na.Abrox,但没用


有什么帮助吗?

df如果您想尝试并比较上述几种插值方法,您可以使用
软件包中的
na.interpolation()
函数

对于线性插值:

Time    Flux    int corr    dat    
7/16/2017 18:46 NA  403.5413091 422.745436  NA    
7/16/2017 21:52 NA  421.5796345 447.6726631 NA   
7/16/2017 23:16 4.51263406  NA  NA  NA  
7/17/2017 4:03  NA  410.0796897 420.4392183 NA  
7/17/2017 5:13  NA  NA  NA  2.316481462  
7/17/2017 5:27  2.291454049 NA  NA  NA  
7/17/2017 18:57 NA  363.5271212 408.7056493 NA  
7/17/2017 19:25 4.568703192 NA  NA  NA  
7/17/2017 23:58 NA  NA  NA  7.11779784  
7/18/2017 2:59  NA  398.9564539 421.8799971 NA  
7/18/2017 3:27  3.392520428 NA  NA  NA  
7/18/2017 3:59  NA  NA  NA  2.953349661  
library("imputeTS")
na.interpolation(df, option = "linear")
library("imputeTS")
na.interpolation(df, option = "spline")
对于样条曲线插值:

Time    Flux    int corr    dat    
7/16/2017 18:46 NA  403.5413091 422.745436  NA    
7/16/2017 21:52 NA  421.5796345 447.6726631 NA   
7/16/2017 23:16 4.51263406  NA  NA  NA  
7/17/2017 4:03  NA  410.0796897 420.4392183 NA  
7/17/2017 5:13  NA  NA  NA  2.316481462  
7/17/2017 5:27  2.291454049 NA  NA  NA  
7/17/2017 18:57 NA  363.5271212 408.7056493 NA  
7/17/2017 19:25 4.568703192 NA  NA  NA  
7/17/2017 23:58 NA  NA  NA  7.11779784  
7/18/2017 2:59  NA  398.9564539 421.8799971 NA  
7/18/2017 3:27  3.392520428 NA  NA  NA  
7/18/2017 3:59  NA  NA  NA  2.953349661  
library("imputeTS")
na.interpolation(df, option = "linear")
library("imputeTS")
na.interpolation(df, option = "spline")
对于斯泰曼插值:

Time    Flux    int corr    dat    
7/16/2017 18:46 NA  403.5413091 422.745436  NA    
7/16/2017 21:52 NA  421.5796345 447.6726631 NA   
7/16/2017 23:16 4.51263406  NA  NA  NA  
7/17/2017 4:03  NA  410.0796897 420.4392183 NA  
7/17/2017 5:13  NA  NA  NA  2.316481462  
7/17/2017 5:27  2.291454049 NA  NA  NA  
7/17/2017 18:57 NA  363.5271212 408.7056493 NA  
7/17/2017 19:25 4.568703192 NA  NA  NA  
7/17/2017 23:58 NA  NA  NA  7.11779784  
7/18/2017 2:59  NA  398.9564539 421.8799971 NA  
7/18/2017 3:27  3.392520428 NA  NA  NA  
7/18/2017 3:59  NA  NA  NA  2.953349661  
library("imputeTS")
na.interpolation(df, option = "linear")
library("imputeTS")
na.interpolation(df, option = "spline")

如您所见,您只需调整选项参数。

zoo软件包中可能有
NA
填充功能。尝试
库(zoo);apropos(“^na[.]”
和帮助文件。