如何解决矩阵在R中不一致地删除列名称
我有一个名为foo的小函数。当我使用m0运行它时，它会正确显示列名。但是当我将其与m1一起使用时，foo会忽略所有列名称。
有解决办法吗？
library(lme4)
library(Matrix)
sng <- read.csv('https://raw.githubusercontent.com/rnorouzian/e/master/sng.csv')
m0 <- lmer(y ~ A * B * C + (A * B * C | group),data = sng)
m1 <- lmer(y ~ A * B * C + (A * B * C || group),data = sng)
foo <- function(fit){
vc <- VarCorr(fit)
as.matrix(Matrix::bdiag(vc))
}
# EXAMPLES OF USE:
foo(m0) # SHOWS COLUMNAMES FINE :-)
foo(m1) # OMITS COLUMNNAMES ALL :-(
解决方法
尝试这种方法。输出矩阵和VarCorr()中列表的长度似乎是一个问题。这里的代码：
library(lme4)
library(Matrix)
#Data and models
sng <- read.csv('https://raw.githubusercontent.com/rnorouzian/e/master/sng.csv')
m0 <- lmer(y ~ A * B * C + (A * B * C | group),data = sng)
m1 <- lmer(y ~ A * B * C + (A * B * C || group),data = sng)
#Function
foo <- function(fit){
vc <- VarCorr(fit)
if(length(vc)==1)
{
y <- as.matrix(Matrix::bdiag(vc))
} else
{
z <- do.call(rbind,vc)
y <- as.matrix(Matrix::bdiag(vc))
dimnames(y)[[1]] <- rownames(z)
dimnames(y)[[2]] <- rownames(z)
}
return(y)
}
#Apply
foo(m0)
foo(m1)
输出：
foo(m0)
(Intercept) A B C A:B
(Intercept) 3.55516422891 0.2559261707 -0.0472493899 0.00321219209 -0.02924403667
A 0.25592617067 4.0133838788 0.0772138992 -0.03546219301 -0.22207717925
B -0.04724938991 0.0772138992 6.4063596371 -1.16254872282 -0.42778740468
C 0.00321219209 -0.0354621930 -1.1625487228 4.78167840574 -0.05459620260
A:B -0.02924403667 -0.2220771793 -0.4277874047 -0.05459620260 0.04574366496
A:C -0.03399653992 -0.2008053942 0.3219439970 -0.42927661072 -0.00100945652
B:C -0.02404787917 0.0212759619 -0.1454033407 -0.43345150872 0.02116923485
A:B:C 0.00586240974 0.0206112404 0.0140531649 0.04266309961 -0.00336982403
A:C B:C A:B:C
(Intercept) -0.03399653992 -0.02404787917 0.005862409744
A -0.20080539424 0.02127596189 0.020611240433
B 0.32194399704 -0.14540334071 0.014053164881
C -0.42927661072 -0.43345150872 0.042663099613
A:B -0.00100945652 0.02116923485 -0.003369824029
A:C 0.05859594675 0.02996839148 -0.004072087992
B:C 0.02996839148 0.05038262309 -0.004808881907
A:B:C -0.00407208799 -0.00480888191 0.000590970743
foo(m1)
(Intercept) A B C A:B A:C B:C A:B:C
(Intercept) 3.29966179 0.000000000 0.000000000 0.0000000 0 0.00000000e+00 0.0000000000 0
A 0.00000000 0.914972854 0.000000000 0.0000000 0 0.00000000e+00 0.0000000000 0
B 0.00000000 0.000000000 0.467647434 0.0000000 0 0.00000000e+00 0.0000000000 0
C 0.00000000 0.000000000 0.000000000 1.1369602 0 0.00000000e+00 0.0000000000 0
A:B 0.00000000 0.000000000 0.000000000 0.0000000 0 0.00000000e+00 0.0000000000 0
A:C 0.00000000 0.000000000 0.000000000 0.0000000 0 6.72771167e-08 0.0000000000 0
B:C 0.00000000 0.000000000 0.000000000 0.0000000 0 0.00000000e+00 0.0013880372 0
A:B:C 0.00000000 0.000000000 0.000000000 0.0000000 0 0.00000000e+00 0.0000000000 0
构造matrix后，我们检查dimnames是否为NULL。在这种情况下，请从“ VarCorr”对象获取dimnames attributes并将其作为dimnames分配给输出matrix
foo <- function(fit){
vc <- VarCorr(fit)
out <- as.matrix(Matrix::bdiag(vc))
if(is.null(unlist(dimnames(out)))) {
nm <- unlist(lapply(vc,function(x) attributes(x)$dimnames[1]))
dimnames(out) <- list(nm,nm)
}
out
}
-测试
foo(m0)
(Intercept) A B C A:B A:C B:C A:B:C
(Intercept) 3.7562550486 0.02806147 -0.07385379 -0.188350388 0.072254892 -0.045056715 -0.023888893 0.0003069446
A 0.0280614731 3.99805818 -0.04527522 -0.091514845 -0.230125332 -0.198148495 0.032987776 0.0205313838
B -0.0738537902 -0.04527522 6.58615173 -1.351344388 -0.457616613 0.340081875 -0.154002255 0.0156069012
C -0.1883503881 -0.09151484 -1.35134439 4.748865101 -0.004621977 -0.396069722 -0.396633305 0.0362619475
A:B 0.0722548916 -0.23012533 -0.45761661 -0.004621977 0.049207775 -0.005718505 0.017880341 -0.0031794465
A:C -0.0450567147 -0.19814850 0.34008188 -0.396069722 -0.005718505 0.053356862 0.023347554 -0.0032476293
B:C -0.0238888932 0.03298778 -0.15400225 -0.396633305 0.017880341 0.023347554 0.045604619 -0.0040810919
A:B:C 0.0003069446 0.02053138 0.01560690 0.036261947 -0.003179446 -0.003247629 -0.004081092 0.0005059711
foo(m1)
(Intercept) A B C A:B A:C B:C A:B:C
(Intercept) 2.26533 0.0000000 0.0000000 0.000000 0.000000e+00 0.00000e+00 0.000000000 0
A 0.00000 0.8446554 0.0000000 0.000000 0.000000e+00 0.00000e+00 0.000000000 0
B 0.00000 0.0000000 0.4905843 0.000000 0.000000e+00 0.00000e+00 0.000000000 0
C 0.00000 0.0000000 0.0000000 1.169259 0.000000e+00 0.00000e+00 0.000000000 0
A:B 0.00000 0.0000000 0.0000000 0.000000 4.816447e-08 0.00000e+00 0.000000000 0
A:C 0.00000 0.0000000 0.0000000 0.000000 0.000000e+00 7.71255e-09 0.000000000 0
B:C 0.00000 0.0000000 0.0000000 0.000000 0.000000e+00 0.00000e+00 0.001425746 0
A:B:C 0.00000 0.0000000 0.0000000 0.000000 0.000000e+00 0.00000e+00 0.000000000 0
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