% Assume you determined xdata and ydata experimentally function logistic_renkou clc clear all xdata = [1790 1800 1810 1820 1830 1840 1850 1860 1870 1880 ... 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000]; ydata = [3.9 5.3 7.2 9.6 12.9 17.1 23.2 31.4 38.6 50.2 62.9 76.0 ... 92.0 106.5 123.2 131.7 150.7 179.3 204.0 226.5 251.4 281.4]; a0 = [400 0.02]; % 初始猜测值 [a, resnorm] = lsqcurvefit(@logistic,a0,xdata,ydata) yfit = a(1)./(1+(a(1)/3.9-1)*exp(-a(2)*(xdata-1790))); plot(xdata,ydata,'*b',xdata,yfit,'-r') function y = logistic(a,xdata) y = a(1)./(1+(a(1)/3.9-1)*exp(-a(2)*(xdata-1790)));
以上代码，用lsqcurvefit函数，求解下列方程，返回的a包含了所求的方程参数。
xdata和ydata是需要拟合的x、y值。
y = a(1)./(1+(a(1)/3.9-1)*exp(-a(2)*(xdata-1790)));