如何在R中使用两个输入创建函数？
要创建具有两个输入的函数，我们只需要在函数内部提供两个不同的参数即可。例如，如果我们要创建一个函数来查找a+b的平方，则可以在函数内部使用x和y。查看以下示例，了解我们如何做到这一点。
例1
> F<-function(x,y){x^2+y^2+2*x*y}
> F(x=1,y=1)
> F(x=2,y=3)
> F(x=c(1,2),y=c(2,3))输出结果
[1] 4 [1] 25 [1] 9 25
示例
> F(x=rpois(50,2),y=rpois(50,7))
输出结果
[1] 36 169 121 36 49 100 144 169 144 81 100 256 121 121 36 64 49 225 121 [20] 16 64 100 36 64 36 144 49 25 196 64 324 196 144 100 81 49 196 121 [39] 16 256 81 100 64 324 81 64 144 81 121 81
示例
> F(x=rpois(120,5),y=rpois(120,10))
输出结果
[1] 256 169 256 225 324 81 196 169 196 121 256 196 441 361 289 144 196 441 [19] 225 144 169 625 169 100 256 144 225 144 100 196 324 169 196 144 121 225 [37] 289 400 196 400 144 256 256 196 144 169 289 225 324 400 196 196 289 121 [55] 256 256 400 169 361 225 324 144 169 144 121 169 169 361 225 169 324 289 [73] 441 196 100 144 64 196 100 121 529 289 289 196 16 400 196 289 196 441 [91] 289 324 169 225 256 225 100 225 225 289 289 81 121 256 289 324 361 361 [109] 196 225 225 324 225 81 225 256 169 144 144 361
例2
> F_1<-function(x,y){x+y-2*x*y}
> F_1(x=2,y=3)
> F_1(x=75,y=83)输出结果
[1] -7 [1] -12292
示例
> F_1(x=rpois(120,5),y=rpois(120,10))
输出结果
[1] -67 -7 -93 -97 -73 -76 -94 -38 -46 -40 -4 -159 -57 -6 -32 [16] -60 -126 -40 -112 -137 -22 -84 -49 -218 -45 -17 -32 -103 -49 -52 [31] -31 -149 -112 -149 -73 -40 -49 -31 -47 -22 -85 -19 -172 -60 -58 [46] -137 -172 -62 -60 -37 -115 -7 -84 -93 -148 -82 -123 -159 -188 -66 [61] -32 -108 -94 -52 -104 -137 -12 -9 -17 -77 -80 -112 -27 -58 -71 [76] -71 -82 -136 -67 -71 -45 -19 -175 -82 -67 -49 -82 -52 -37 -31 [91] -66 -66 -97 -62 -42 -37 -112 -172 -217 -49 -115 -172 -139 -101 -115 [106] -121 -22 -93 -62 -195 -76 -49 -112 -66 13 -31 -142 -178 -22 -121
示例
> F_1(x=sample(0:9,100,replace=TRUE),y=sample(0:9,100,replace=TRUE))
输出结果
[1] -22 -31 -49 8 -37 -32 -38 -49 -22 -31 -84 -8 -17 2 -31 [16] -25 -25 7 -45 -32 -27 -31 -49 -58 -22 -19 -110 -58 5 -4 [31] -25 -59 -76 -25 -67 -93 -58 -58 -4 -127 -49 1 -1 -2 9 [46] -31 -27 -59 -58 6 -93 -3 3 -67 -49 -7 2 -22 -42 -16 [61] -3 -3 -3 -84 4 -8 -49 -17 0 -32 -6 -144 -17 6 -38 [76] -144 -8 -97 2 -10 0 -10 -5 -17 -25 -110 -10 -52 -76 -84 [91] -40 -7 -10 -67 -110 -37 2 -45 -22 -17
例子3
> F_2<-function(x,y){log(x)*log(y)}
> F_2(x=75,y=83)
> F_2(x=7,y=4)输出结果
[1] 19.07829 [1] 2.697604
示例
> F_2(x=rpois(120,5),y=rpois(120,10))
输出结果
[1] 3.444812 2.413898 2.882718 2.899301 4.788091 -Inf 1.348802 2.284500 [9] 2.817885 0.000000 2.975097 3.936898 4.125679 4.991161 2.729949 4.296452 [17] 2.899301 2.882718 2.413898 1.662094 3.444812 3.486603 4.986283 5.178851 [25] 4.480624 2.137801 3.175398 4.480624 0.000000 4.728556 2.634357 2.883726 [33] 3.046000 5.268714 2.882718 2.529648 1.768148 4.296452 3.999303 3.936898 [41] 4.835405 2.284500 2.634357 2.883726 1.829255 5.135368 3.754155 4.480624 [49] 3.444692 3.192061 4.835405 2.634357 4.569000 1.596030 4.986283 3.936898 [57] 4.728556 3.725859 3.131822 4.324077 3.046000 3.725859 2.483906 5.395209 [65] 4.788091 3.046000 4.595772 0.000000 2.483906 2.413898 3.486603 4.569000 [73] 2.137801 3.486603 3.210402 2.883726 4.452355 2.284500 4.125679 4.991161 [81] 5.729614 1.523000 3.936898 3.346732 6.384121 1.241953 3.999303 3.927668 [89] 4.247399 4.569000 4.728556 2.634357 0.000000 2.817885 3.444812 5.167218 [97] 5.333662 4.128127 2.231155 4.827796 2.284500 3.486603 4.569000 3.131822 [105] 3.555775 3.725859 3.046000 2.882718 4.128127 5.135368 4.125679 0.000000 [113] 3.859264 2.137801 3.859264 -Inf 5.721709 4.967812 3.444812 1.523000
示例
> F_2(x=rnorm(50,5,1),y=rnorm(50,10,2.1))
输出结果
[1] 4.568522 3.317414 2.464067 4.791476 4.372595 4.210160 3.526032 2.775343 [9] 3.761276 4.777044 3.505528 3.777687 4.093626 4.725572 2.424238 2.840074 [17] 3.634834 2.929286 3.752320 3.202556 4.275540 4.242939 3.874150 2.951899 [25] 2.933451 3.174667 2.880886 2.045396 4.143767 4.197051 3.701025 3.295414 [33] 2.474207 3.409486 3.039707 3.671767 3.643574 3.970818 3.783388 3.144845 [41] 2.945385 4.001539 2.084827 3.902450 3.525883 3.969045 3.836904 2.683285 [49] 3.727207 3.618169
示例
> F_2(x=runif(50,2,10),y=runif(50,1,3))
输出结果
[1] 2.21564775 0.96637493 1.05330228 1.32946783 2.03839496 1.31868294 [7] 1.38606698 0.60719155 0.43734519 1.39025166 1.67255979 1.18302346 [13] 1.88085789 1.33322258 1.85156672 1.48801903 0.98881685 1.56873098 [19] 0.53751024 0.21240764 1.75668136 1.23090144 1.34516355 1.27257248 [25] 1.97594694 1.12983156 1.26123428 2.19592443 0.52055000 0.78032868 [31] 1.11360152 1.08312234 1.18208915 0.48889271 0.13233468 0.49593395 [37] 1.49938567 1.71066941 1.43949609 1.63249440 0.05952467 1.10418018 [43] 0.39259085 0.21020499 0.59461948 1.78345240 2.24597820 1.99940740 [49] 0.62821888 1.40809854