ersetzen Sie fehlende Werte Zeile weise durch einen Vektor

Question

Ich arbeite daran, fehlende Werte in einem Dataset zu unterwerfen. Ich habe ein Vorhersagemodell, das die Werte erzeugen kann, um das Vermisste zu unterstellen. Wenn ich die Imputation mit dfm [is.na (dfm)] < -impute durchführe, werden die Werte spaltenweise berechnet. Aber ich muss Reihenweise unterstellen, also habe ich die Datenmatrix umgesetzt. Meine Frage ist, gibt es eine elegante Möglichkeit, dies zu tun, ohne die Matrix zu transponieren? Hier ist ein Code mit reproduzierbarem Beispiel.

 set.seed(1) 
     r=5 
     c=4 
     df<-matrix(runif(r*c), ncol=c) 
     df 
      [,1]  [,2]  [,3]  [,4] 
[1,] 0.2655087 0.89838968 0.2059746 0.4976992 
[2,] 0.3721239 0.94467527 0.1765568 0.7176185 
[3,] 0.5728534 0.66079779 0.6870228 0.9919061 
[4,] 0.9082078 0.62911404 0.3841037 0.3800352 
[5,] 0.2016819 0.06178627 0.7698414 0.7774452 

    d=dim(df) 
    p=0.30 

    #### generate missing data matrix by replacing some values by NAs 
    dfm<-df 
    dfm[matrix(rbinom(prod(d), size=1,prob=p)==1,nrow=d[1])]<-NA 
    dfm 
      [,1]  [,2]  [,3]  [,4] 
[1,]  NA 0.89838968 0.2059746 0.4976992 
[2,] 0.3721239 0.94467527 0.1765568  NA 
[3,] 0.5728534 0.66079779 0.6870228 0.9919061 
[4,] 0.9082078   NA 0.3841037  NA 
[5,] 0.2016819 0.06178627  NA 0.7774452 

    # generate values to impute the missing 
impute<-rgamma(sum(is.na(dfm)),shape=1,scale=0.5) 
    impute 
[1] 0.6804725 0.6029941 0.2770577 0.6035013 0.7812393 

#imputes columnwise 
    dfm[is.na(dfm)]<-impute 
    dfm 
      [,1]  [,2]  [,3]  [,4] 
[1,] 0.6804725 0.89838968 0.2059746 0.4976992 
[2,] 0.3721239 0.94467527 0.1765568 0.6035013 
[3,] 0.5728534 0.66079779 0.6870228 0.9919061 
[4,] 0.9082078 0.60299409 0.3841037 0.7812393 
[5,] 0.2016819 0.06178627 0.2770577 0.7774452 

#impute rowwise 
     tdfm<-t(dfm) 
    tdfm[is.na(tdfm)]<-impute 
    tdfm 
      [,1]  [,2]  [,3]  [,4]  [,5] 
[1,] 0.6804725 0.3721239 0.5728534 0.9082078 0.20168193 
[2,] 0.8983897 0.9446753 0.6607978 0.2770577 0.06178627 
[3,] 0.2059746 0.1765568 0.6870228 0.3841037 0.78123933 
[4,] 0.4976992 0.6029941 0.9919061 0.6035013 0.77744522 

     dfm.fill<-t(tdfm) 
     dfm.fill 

      [,1]  [,2]  [,3]  [,4] 
    [1,] 0.6804725 0.89838968 0.2059746 0.4976992 
    [2,] 0.3721239 0.94467527 0.1765568 0.6029941 
    [3,] 0.5728534 0.66079779 0.6870228 0.9919061 
    [4,] 0.9082078 0.27705769 0.3841037 0.6035013 
    [5,] 0.2016819 0.06178627 0.7812393 0.7774452 

Answer 1

Verwenden which stattdessen zusammen mit arr.ind, so dass Sie erste Zeile sortieren.

Beispiel:

test1 <- matrix(1:12, 3, 4, byrow = TRUE) 
test1[c(1, 3, 8, 6, 10)] <- NA 
test2 <- test1 

impute <- c(-1, -4, -7, -9, -10) 

## What you are currently doing--column-wise 
test1[is.na(test1)] <- impute 
test1 
#  [,1] [,2] [,3] [,4] 
# [1,] -1 2 3 -10 
# [2,] 5 6 -9 8 
# [3,] -4 -7 11 12 

## What it sounds like you want--row-wise 
nas <- which(is.na(test2), arr.ind = TRUE) 
test2[nas[order(nas[, "row"]), ]] <- impute 
test2 
#  [,1] [,2] [,3] [,4] 
# [1,] -1 2 3 -4 
# [2,] 5 6 -7 8 
# [3,] -9 -10 11 12