將S形曲線擬合到R中的數據

Question

我想將S型函數擬合到我的數據中，我已經按照類似類似的方法嘗試過： 使用R來擬合S型曲線問題是我的曲線太平坦了，所以沒有達到我的曲線的上限數據（我希望它至少在y軸上達到2或2.3，然后離開圖表）。 您是否有任何提示我必須更改代碼？

提前致謝！

此處的數據（實際上是更多點，因此，如果擬合曲線剛好達到y值1.5時，它將看起來是有線的）：

T<- c(1.45151262, 1.23861251, 2.25986937, 1.50269889, 1.96593223, 1.25365243, 1.98465413, 1.96593223, 0.98585134, 1.45151262,  1.23861251, 2.25986937, 1.96593223, 1.96593223, 2.53257897, 0.53892040, 0.39919629,  0.49431555, 0.37490131,  0.61959698,  1.30069888,  0.34356933,  0.32231250,  0.60307860,  0.46739360,  0.23849933,  0.22491460, 0.18751264,  0.43795313,  0.35338655,  0.44306278, -0.04577398,  0.23924335,  0.36656968,  0.17550798,  0.39912386, 0.86993214,  0.70492281,  1.09849071,  1.49913528,  0.99460365,  0.48011272,  0.73764538,  2.04877202,  0.88241166,1.08291537,  1.58361191,  1.20293826,  1.37084470)

W<-c(-1.100000, -1.150000, -0.850000, -0.850000, -0.650000, -0.700000, -0.650000, -0.650000, -0.700000, -1.100000, -1.150000, -0.850000, -0.650000, -0.650000, -0.750000, -1.250000, -1.350000, -1.200000, -1.266667, -0.950000, -1.000000, -1.150000, -1.100000, -1.150000, -1.200000, -2.000000, -1.700000, -1.550000, -2.150000, -1.850000, -1.600000, -1.500000, -1.500000, -1.550000, -1.700000, -0.650000, -0.550000, -1.100000, -0.500000, -0.950000,       -0.950000, -0.800000, -1.050000, -0.600000, -0.750000, -1.200000, -0.700000, -0.600000, -0.950000)

我使用的代碼：

plot(T~W)

M1 <- nls(T ~a/(1 + exp(-b * (W-c)) ), start=list(a=2.5,b=1,c=-1))

lines(seq(-6,0, length.out = 100), predict(M1, newdata = data.frame(W = seq(-6,0, length.out = 100))))

Answer 1

這可能不足以滿足您的需求，但是我能夠使用下面的曲線圖和參數統計量來擬合Lomolino Sigmoidal方程：

T = a / (1.0 + pow(b, ln(c/W))) + Offset

Fitting target of lowest sum of squared absolute error = 1.0217387563792354E+01

a =  1.2760743831471755E+00
b =  2.8233200470290357E-05
c = -1.1164548271725272E+00
Offset =  2.4350187846845511E-01