每月数据的季节性分解，包括 r 中的 NA [英] Seasonal decompose of monthly data including NA in r

问题描述

我需要你们的帮助来分解我的具有季节性的月度数据，但它不起作用，因为没有删除 NA 值..可能还有另一个问题.请查看我的数据和错误如下.

I need help from you guys to decompose my monthly data which have seasonality, but it does not work because NA values are not removed..There may be another problem. Please look at my data and errors as below.

    ts.monthly<-ts(monthly$rBC.median, frequency=12, start=c(2006, 4))
    ts.monthly
        Jan        Feb        Mar        Apr        May        Jun
    2006                                   5.1656479  6.2847959 19.4833690
    2007  1.4252665  2.9127775  2.8912652  7.5326158  8.6182227 23.2129310
    2008         NA  1.8200842  1.3488755  2.0700927  5.3541366  8.6916708
    2009  1.2531161  1.5075780  2.4955524 10.6724704 10.1367162 16.0362127
    2010  0.8850190  2.4974866  1.8459976  9.2297697  3.8203789  7.1492986
    2011  2.6990434  0.4570701  1.3787403  5.8739804  4.1669501 13.2228535
    2012         NA  2.0670538  1.3758499 11.7306663  4.1248775 12.3604423
                Jul        Aug        Sep        Oct        Nov        Dec
    2006  9.8028986  7.8167810  2.1333807  2.5777504  1.9022561  2.7254065
    2007  4.2121577  8.8604768 12.0017155  4.0978332  1.6053110         NA
    2008  5.7338211  9.7432563  4.6548508  1.3589789  0.9650082  1.2788504
    2009 11.7632775 11.2299683  1.6229679  1.0333217  1.0481580  1.0734208
    2010  3.5996501  4.3245873  4.4586863  1.6403104  2.8622518  1.2564256
    2011  3.0463918  7.1515472  6.5613683  1.3715623  1.9757217  5.4901524
    2012 11.1010563  3.6220968  2.2597341  

   ts.monthly=na.omit(ts.monthly)  
    Error in na.omit.ts(ts.monthly) : time series contains internal NAs
   ts.monthly.com<-decompose(ts.monthly)
    Error in na.omit.ts(x) : time series contains internal NAs
   ts.monthly$seasonal
    Error in ts.monthly$seasonal : $ operator is invalid for atomic vectors

我不明白为什么 na.omit 不起作用.. 我该如何治疗这个 NA??

I do not understand why na.omit does not work.. how can I treat this NA??

最后，在使用分解"函数后，我想只取趋势"而没有季节性，然后应用 sen 的斜率估计器得到线性趋势的斜率.会有用吗??

Finally, after using a function "decompose", I want to take only "trend" without seasonality, and then apply sen's slope estimator to get a slope for linear trend. It will work??

非常感谢您的帮助.

推荐答案

首先使用 zoo 包中的 na.StructTS 尝试使用季节性卡尔曼滤波器填充缺失值:

Try filling in the missing values using a seasonal Kalman filter by employing na.StructTS from the zoo package first:

library(zoo)
decompose(na.StructTS(ts.monthly))

zoo 还有许多其他 na. 函数:na.aggregate、na.approx、na.fill、na.locf、na.spline、na.StructTS、na.trim.

zoo has many other na. functions as well: na.aggregate, na.approx, na.fill, na.locf, na.spline, na.StructTS, na.trim.

这篇关于每月数据的季节性分解，包括 r 中的 NA的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！