如何仅将“矩阵”“数组”转换为矩阵

Question

我对 R 很陌生，正在努力创建一个矩阵。我的教育目标是创建一个方差-协方差矩阵以供进一步分析。我创建了一个自定义函数并获得了所需格式的输出，但它显示 "matrix" "array." 实际上，我只想要 matrix 中的输出。

关于数据： 数据是实际数据的片段。有3个复制（rep）和3个处理（treat），3个字符（dtf、rpp、ppr）。

功能是计算基因型方差-表型矩阵。

data<- structure(list(rep = c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L), 
                      treat = c("1", "1", "1", "2", "2", "2", "3", "3", "3"), 
                      dtf = c(51L, 51L, 52L, 52L, 52L, 52L, 52L, 58L, 52L), 
                      rpp = c(4.6667, 6.4, 7.25, 3.5, 6.1, 6.5556, 4.1429, 4, 3.5), 
                      ppr = c(2.6111, 4.8333, 5.463, 3.0167, 5.9, 4.7778, 2.7381, 2.7778, 4.1389)), 
                      row.names = c(NA, 9L), 
                      class = "data.frame")
# Gen Var-Cov
gvcov<- function (data, genotypes, replication) {
  convrt<- function(data1) {
    data1<- as.data.frame(sapply(data1, as.numeric))
    data1<- as.list(data1)
    return(data1)
  }
  datam<- convrt(data)
  colnumber<- ncol(data)
  headings<- names(data)
  analysis<- function(genotypes, replication, trait1, trait2) {
    genotypes<- as.factor(genotypes)
    replication<- as.factor(replication)
    sumch1<- tapply(trait1, genotypes, sum)
    sumch2<- tapply(trait2, genotypes, sum)
    sumr1<- tapply(trait1, replication, sum)
    sumr2<- tapply(trait2, replication, sum)
    repli<- nlevels(replication)
    genotype<- nlevels(genotypes)
    GT1<- sum(trait1)
    GT2<- sum(trait2)
    CF<- (GT1 * GT2)/(repli * genotype)
    TSP<- round(sum(trait1 * trait2) - CF, 4)  
    GSP<- round((sum(sumch1 * sumch2)/repli) - CF, 4) 
    RSP<- round((sum(sumr1 * sumr2)/genotype) - CF, 4)
    ESP<- TSP - GSP - RSP
    DFR<- repli - 1 
    DFG<- genotype - 1 
    DFE<- DFR * DFG 
    RMP<- round(RSP/DFR, 4)
    GMP<- round(GSP/DFG, 4)
    EMP<- round(ESP/DFE, 4)
    ECov<- EMP
    GCov<- round((GMP - EMP)/repli, 4)
    return(GCov)
  }
  # matrix
  genetic.cov<- c()
  index = 0
  for (i in 1:(colnumber)) {
    for (j in 1:colnumber) {
      index = index + 1
      genetic.cov[index]<- analysis(genotypes, replication, 
                                    datam[[i]], datam[[j]])
    }
  }
  matrix1<- matrix(genetic.cov, nrow = colnumber, 
                   dimnames = list(headings, headings))
  return(matrix1)
}
a<- gvcov(d[3:8], d$treat, d$rep)

class(a)