Question

我试图找到对Guassian核密度估计量贡献最大和最小的值。我已经编写了一个函数来查找这些函数，但是当我运行它时，我得到了一个max的多个值。我认为这可能与有效数字的数量有关，所以我增加了但没有改变。

任何人都可以提供一些见解吗？

#Create a vector with Brainsize-Small Litter Size Data:
Y_i<-c(0.42, 0.86, 0.88, 1.11, 1.34, 1.38, 1.42, 1.47, 1.63,1.73, 2.17, 2.42, 2.48, 2.74, 2.74, 2.79, 2.90, 3.12,3.18, 3.27, 3.30, 3.61, 3.63, 4.13, 4.40, 5.00, 5.20,5.59, 7.04, 7.15, 7.25, 7.75, 8.00, 8.84, 9.30, 9.68,10.32, 10.41, 10.48, 11.29, 12.30, 12.53, 12.69, 14.14, 14.15,14.27, 14.56, 15.84, 18.55, 19.73, 20.00)

#Create a kernel density estimator function:
kern<-function(data=0,effOf=0,bw=0){
z<-rep(0,length(data))
k<-rep(0,length(data))

for(i in data){
 z[i]=((effOf-data[i])/bw)
}

for(j in z){
 k[j]=(1/sqrt(2*pi))*exp(-(z[j]^2/2))/(length(data)*bw)
}

min=min(k)
imin=which(k==min)
ymin=data[imin]

max=max(k)
imax=which(k==max)
ymax=data[imax]

print(paste("The minimum contributor is value",ymin))
print(paste("The maximum contributor is value",ymax))

estimate=sum(k)
return(estimate)
}

#(a.)Use KDE function to estimate f(16)
kern(Y_i,16,3)

这是输出 - 请记住，我只想要一个最大值：

 [1] "The minimum contributor is value 0.42"  "The minimum contributor is value 0.86" 
 [3] "The minimum contributor is value 0.88"  "The minimum contributor is value 1.38" 
 [5] "The minimum contributor is value 1.42"  "The minimum contributor is value 1.47" 
 [7] "The minimum contributor is value 1.63"  "The minimum contributor is value 1.73" 
 [9] "The minimum contributor is value 2.17"  "The minimum contributor is value 2.42" 
[11] "The minimum contributor is value 2.48"  "The minimum contributor is value 2.74" 
[13] "The minimum contributor is value 2.74"  "The minimum contributor is value 2.79" 
[15] "The minimum contributor is value 2.9"   "The minimum contributor is value 3.12" 
[17] "The minimum contributor is value 3.18"  "The minimum contributor is value 3.27" 
[19] "The minimum contributor is value 3.3"   "The minimum contributor is value 3.61" 
[21] "The minimum contributor is value 3.63"  "The minimum contributor is value 4.13" 
[23] "The minimum contributor is value 4.4"   "The minimum contributor is value 5"    
[25] "The minimum contributor is value 5.2"   "The minimum contributor is value 5.59" 
[27] "The minimum contributor is value 7.04"  "The minimum contributor is value 7.15" 
[29] "The minimum contributor is value 7.25"  "The minimum contributor is value 7.75" 
[31] "The minimum contributor is value 8"     "The minimum contributor is value 8.84" 
[33] "The minimum contributor is value 9.3"   "The minimum contributor is value 9.68" 
[35] "The minimum contributor is value 10.32" "The minimum contributor is value 10.41"
[37] "The minimum contributor is value 10.48" "The minimum contributor is value 11.29"
[39] "The minimum contributor is value 12.3"  "The minimum contributor is value 12.53"
[41] "The minimum contributor is value 12.69" "The minimum contributor is value 14.14"
[43] "The minimum contributor is value 14.15" "The minimum contributor is value 14.27"
[45] "The minimum contributor is value 14.56" "The minimum contributor is value 15.84"
[47] "The minimum contributor is value 18.55" "The minimum contributor is value 19.73"
[49] "The minimum contributor is value 20"   
[1] "The maximum contributor is value 1.34"
[1] 2.868016e-08

Answer 1

我认为正确的代码应该如下（有两个修改，for循环中的索引不正确导致错误的z和内核值）：

kern<-function(data=0,effOf=0,bw=0){

  z<-rep(0,length(data))
  k<-rep(0,length(data))

  for(i in 1:length(data)){ # iterate through all data points
    z[i]=((effOf-data[i])/bw)
  }

  for(j in 1:length(z)){ # iterate through all z values
    k[j]=(1/sqrt(2*pi))*exp(-(z[j]^2/2))/(length(data)*bw)
  }

  min=min(k)
  imin=which(k==min)
  ymin=data[imin]

  max=max(k)
  imax=which(k==max)
  ymax=data[imax]

  print(paste("The minimum contributor is value",ymin))
  print(paste("The maximum contributor is value",ymax))

  estimate=sum(k)
  return(estimate)
}

#(a.)Use KDE function to estimate f(16)
kern(Y_i,16,3)

[1] "The minimum contributor is value 0.42"
[1] "The maximum contributor is value 15.84"
[1] 0.02254657

R中的多个最小值

1 个答案: