R：绘制法线以与我的数据分布进行比较时出错
我有一个名为Datadiff的向量：R：绘制法线以与我的数据分布进行比较时出错,r,plot,histogram,normal-distribution,R,Plot,Histogram,Normal Distribution,我有一个名为Datadiff的向量： [1] 0.00000 -0.01415 2.68350 -4.26980 -2.28975 -1.27000 6.63400 -3.13965 -1.67050 -0.28920 -0.42435 [12] -1.36785 -1.97000 6.62200 -0.82470 -1.99530 1.84275 -4.70575 3.67150 -1.00900 -1.00205 -0.77350
[1] 0.00000 -0.01415 2.68350 -4.26980 -2.28975 -1.27000 6.63400 -3.13965 -1.67050 -0.28920 -0.42435
[12] -1.36785 -1.97000 6.62200 -0.82470 -1.99530 1.84275 -4.70575 3.67150 -1.00900 -1.00205 -0.77350
[23] -0.86150 -2.12430 2.20255 2.03850 -0.19295 1.83205 2.04300 -3.51635 -3.32000 9.07800 -0.60280
[34] 11.15045 -8.44820 -9.49590 0.13885 -1.06000 3.85800 -1.27255 0.35010 3.38085 -5.70870 5.08605
[45] -6.67000 6.57600 -4.48095 0.05825 3.35215 5.94525 -8.91095 -1.21000 7.99800 -2.21730 13.66610
[56] -20.52355 0.68220 3.64315 -0.46000 4.08800 5.76705 3.88775 -12.32920 -0.08525 -4.10745 -6.70000
[67] 8.73800 5.17880 -8.20225 -1.61770 23.66225 -16.23860 -2.25000 -5.24400 8.21195 19.02100 -1.55330
[78] -10.74680 -13.19870 4.32000 -3.45600 0.29670 2.22515 -1.77935 -0.26525 0.32630 0.37000 10.26200
[89] 5.38240 -15.50855 -0.65105 6.84655 -9.38970 1.70000 5.43200 10.17880 2.98075 -10.85725 -6.22135
[100] -1.89010 -3.46000 -2.29000 4.69180 1.20210 -0.95415 -3.40435 -7.49000 -0.15000 7.49445 -0.14045
[111] 3.35195 -2.63695 0.83655 -12.01000 11.16400 9.18425 -3.91240 6.02935 -2.27235 -4.32110 -3.16000
[122] 1.17000 0.74640 -0.12670 2.26105 0.04115 -2.31855 -2.30000 1.81400 0.68420 -0.94390 0.67445
[133] 7.34260 -8.99235 -3.63000 4.55800 5.04180 -5.30290 0.96565 2.37130 0.33100 -2.53000 6.50400
[144] 2.81535 -0.90240 -2.62860 -3.69285 0.61605 -5.81000 5.32800 -0.39985 0.52635 0.39335 0.56145
[155] -0.92660 -1.53000 10.51400 -3.33635 -4.52020 -1.85500 0.36355 -11.26815 1.62000 10.89000 -0.51330
[166] -9.56000 -1.79115 -14.12515 14.49105 -6.90000 2.76400 19.79725 -1.36595 -5.14430 1.67195 -9.18290
[177] -3.72000 18.14200 -2.22105 -5.47200 -1.74350 7.38740 -2.16620 -12.96000 12.10000 1.05790 4.37990
[188] 1.46360 -1.55485 -5.30650 -3.08000 9.59000 -0.70365 -0.29480 0.08570 -3.14220 -4.90170 -4.05690
[199] 0.82470 -0.61950 0.58260 -8.70000 16.49600 -2.05375 -1.15520 0.74145 0.49035 -9.79180 -1.06000
[210] 9.70800 -2.02660 -0.83785 1.14500 -1.46245 -4.42830 -16.34000 18.55000 1.93415 -3.23050 -3.63245
[221] 7.33200 -5.96870 -0.93000 2.03600 5.73760 -2.35745 5.82470 -2.38335 -5.71340 -7.60000 15.42000
[232] -1.36575 -1.38560 -5.07790 5.94480 -10.58400 -4.41000 11.21400 0.33840 1.42130 -3.75035 7.43265
[243] 2.78635 -15.19000 -1.36800 16.65735 -3.12405 -2.51290 3.51920 -9.63090 -0.95000 21.88000 -6.28715
[254] 6.66370 0.89995 -3.76125 -10.85840 -3.51000 13.74800 -3.02445 0.29100 0.33760 0.13705 -7.97660
[265] -1.15000 6.79400 -3.98745 -1.46300 2.38375 1.73950 -10.64685 -7.78000 15.32400 2.30850 -2.49665
[276] -2.86120 -1.30305 -2.09495 -2.23000 11.44800 -0.74900 0.83135 -3.44695 0.31755 -4.00500 -8.25000
[287] 16.45800 3.01845 1.72375 -3.42175 -2.29725 -4.55095 -8.92000 11.56400 -0.85435 -0.98450 1.37875
[298] -0.05225 -1.79065 -3.24000 6.89800 -2.88615 1.89680 -1.71995 1.23670 4.76065 1.91705 4.91885
[309] -3.09340 -9.62280 -6.96000 10.17000 1.00150 -0.27075 3.60460 3.91925 -12.29470 -0.15000 11.58200
[320] 1.95930 -9.38075 -1.46460 -5.29375 -1.29280 -2.95000 10.18800 -1.85795 -2.52690 3.46760 0.71515
[331] -3.87005 -4.41000 14.17200 5.00880 -1.75035 -7.26945 -4.97815 0.33920 -4.99000 -0.38000 13.42315
[342] 0.44745 -12.82670 5.65645 -1.60595 -4.19000 10.42800 -0.91455 2.01905 -1.22470 -6.72005 -2.37540
[353] -6.62000 11.03000 -0.16420 4.67650 2.10160 -5.40605 -5.63525 -7.84000 13.38400 -4.76505 -2.09520
[364] -0.21815 -5.53800 0.89805 0.84000 -3.79800 15.20915 -5.04190 2.85030 -3.54720 5.66655 -2.09000
[375] -3.51800 -2.05115 4.75600 1.64015 -2.93645 -2.78400 -4.60000 7.83000 7.58955 -4.06370 -3.14205
[386] -1.00330 -0.78590 -3.09000 16.99000 -1.75450 -0.17840 -6.17105 3.67985 -7.73185 -1.45000 -0.48000
[397] -0.03625 0.64765 -0.88770 4.37420 -3.41025 -4.16000 2.30600 3.64675 0.65160 -1.86050 4.44755
[408] -4.64435 0.59000 7.70800 0.13515 -3.63075 4.07175 -3.44855 1.61700 -2.69000 6.99000 -6.32835
[419] 0.06035 0.66905 2.09225 -8.90405 2.90000 -5.14800 1.27180 11.69970 18.22670 -5.02240 -11.80655
[430] -11.48000 22.61800 -2.89710 -21.47555 4.60950 0.11945 -1.44270 -1.49000 2.91800 5.56680 -4.15875
[441] -0.84530 -4.80830 2.38945 0.68000 6.40800 1.46045 6.47015 -3.83785 3.01765 -13.76620 3.80000
[452] 7.04600 -9.70915 5.06240 -4.42255 -4.30895 -0.48565 1.48000 1.01400 0.41325 4.26235 -0.52185
[463] -2.46555 0.05000 -1.16000 -0.26780 2.31460 7.02870 0.74975 -6.08455 -2.63000 2.65200 -5.02335
[474] 2.71820 14.30270 -14.36495 -2.38640 -4.52000 8.25600 -3.06855 -0.76365 4.48095 5.21815 -4.52365
[485] -1.52000 12.16000 -1.96610 8.04025 10.50445 -17.61300 -13.53880 -6.99000 7.25800 9.58530 3.87375
[496] -2.82975 2.68740 -11.12640 -3.71000 -2.09800 11.13375 -4.50495 -4.49020 3.06840 -3.24390 2.42000
[507] 10.54600 -6.76650 -1.39590 2.19665 -2.40210 -2.70515 -4.53000 6.81400 -2.62700 1.78745 -2.80275
[518] 5.00345 -5.79180 -0.41000 3.71200 1.10155 -0.99680 -1.49750 2.46750 -3.66735 -1.33000 1.89400
[529] 2.14050 -0.45820 -2.64025 1.64115 -2.63910 2.86000 -0.43000 -0.02565 -0.69105 0.18560 -0.08540
[540] -2.21505 -2.10000 7.17400 4.28040 -3.66650 -1.47560 1.35750 -2.93310 -2.36000 -0.04400 3.63380
[551] 1.57210 0.75930 -1.84085 -1.37640 -3.31000 4.11800 0.87930 3.56600 -0.25750 -2.47415 -2.73090
[562] -3.30000 5.78600 -3.72375 -0.40445 2.40250 1.75210 -3.30980 -2.22000 4.11600 -1.04385 1.09985
[573] 0.12310 -0.10000 0.85585 -3.19015 2.50105 2.59145 -9.87755 4.65000 4.64000 -0.38080 -2.83590
[584] 2.52765 -0.46655 -1.21260 -1.33000 7.19000 5.16895 -11.32840 5.50915 -0.29850 -4.34405 -1.16000
[595] 1.99200 0.94850 -0.11665 -1.32835 3.87565 -4.49720 -1.83000 10.71400 -3.08910 -2.57270 0.14165
[606] 0.67460 -3.13245 -10.58000 11.04000 4.67700 -0.76965 -8.59540 5.31355 -0.48550 -9.83000 13.65000
[617] 1.98135 -1.52210 -2.02930 -1.18050 -6.26230 4.41000 -1.84800 12.20420 -0.73490 -5.45060 2.30475
[628] -5.93990 -0.98000 8.14800 0.68375 -1.57665 -1.89040 1.30625 -6.66715 -1.09000 5.37200 6.03350
[639] -2.11330 -3.12840 7.26250 -9.10530 -7.88000 6.99800 1.24900 -1.71020 -0.42185 1.02915 -2.83645
[650] -2.63000 5.59000 0.04545 2.03685 5.21010 -2.90810 -7.58070 -0.74000 4.79800 -0.78570 6.57080
[661] -1.00055 0.71075 -8.20515 -2.34000 8.04000 5.03540 3.79530 1.00215 -4.29350 -8.57975 -3.60000
[672] 10.74600 0.03990 -1.48135 1.15855 -2.66635 -6.04255 -1.27000 6.89800 1.07795 -1.42805 -4.52400
[683] 3.48210 -10.79030 1.01000 10.82400 -2.22530 -0.37040 -3.96645 3.98060 -8.26920 4.43000 2.02000
[694] 5.57785 1.46695 -5.79030 1.21475 -4.58515 -0.81000 13.70000 1.10770 4.14880 -6.56570 -3.85860
[705] -5.86435 -2.84000 8.22800 0.06675 -0.60955 -2.53285 1.06340 2.27175 1.30000 7.91000 -11.03340
[716] -4.43140 3.40160 0.42545 -4.02465 -4.39000 14.80000 -11.49595 3.76795 9.23025 -3.32815 -7.07725
[727] -2.19000 11.81600 0.91175 -4.06940 -3.73460 -1.05750 -6.47590 -0.52000 7.66400 6.21025 -2.67520
[738] 1.26305 -1.17585 -6.75250 -4.32000 11.27200 -5.91505 1.08715 -0.00055 -3.66290 3.58325 -6.39000
[749] 13.22600 0.88190
histogram <- hist(Datadiff, breaks = 40)
multiplier2 <- unique(histogram$counts/histogram$density)[1]
lines(x = Datadiff, dnorm(Datadiff, sd = sd(Datadiff))*multiplier2, lwd = 3, lty = 2)
直方图您可以使用曲线
。在直方图中设置freq=FALSE
，以获得两个图中一致的密度
hist(Datadiff, breaks=40, freq=FALSE)
curve(dnorm(x, mean=mean(Datadiff), sd=sd(Datadiff)),
add=TRUE, col=2, lty=2)
legend("topright", c("empirical", "theoretical normal"), cex=.8, lty=1:2, col=1:2)
（如果要与标准正常值进行比较，请不要使用mean=mean（Datadiff），sd=sd（Datadiff）
，让您的dnorm（.）
默认为mean=0，sd=1
）
生产
资料
Datadiff您可以使用curve
。在直方图中设置freq=FALSE
，以获得两个图中一致的密度
hist(Datadiff, breaks=40, freq=FALSE)
curve(dnorm(x, mean=mean(Datadiff), sd=sd(Datadiff)),
add=TRUE, col=2, lty=2)
legend("topright", c("empirical", "theoretical normal"), cex=.8, lty=1:2, col=1:2)
（如果要与标准正常值进行比较，请不要使用mean=mean（Datadiff），sd=sd（Datadiff）
，让您的dnorm（.）
默认为mean=0，sd=1
）
生产
资料
Datadiff如果您想保持Y轴上的频率而不是密度，只需使用dnorm
中观察范围内的序列即可
你的旧代码
histogram <- hist(Datadiff, breaks = 40)
multiplier2 <- unique(histogram$counts/histogram$density)[1]
您也可以用观察到的平均值mean=mean（Datadiff）
如果要保持Y轴上的频率而不是密度，只需在dnorm
中的观察范围内使用序列即可
你的旧代码
histogram <- hist(Datadiff, breaks = 40)
multiplier2 <- unique(histogram$counts/histogram$density)[1]
您也可以用观察到的平均值mean=mean（Datadiff）
lines(x = seq1, dnorm(seq1,sd = sd(Datadiff))*multiplier2, lwd = 3, lty = 2)