(fm=lm(y~x1+x2+x3+x4,data=d4.3)) Call: lm(formula = y ~ x, data = yx) Coefficients: (Intercept) x -1.197 1.116这段代码有什么用处?
时间: 2023-05-18 14:06:39 浏览: 50
这段代码是用来进行线性回归分析的,其中 y 代表因变量,x1、x2、x3、x4 代表自变量,fm=lm(y~x1 x2 x3 x4,data=d4.3) 表示将自变量 x1、x2、x3、x4 与因变量 y 进行线性回归分析,并将结果保存在 fm 中。而 (Intercept) 和 x -1.197 1.116 则是回归方程的截距和斜率。
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t=0:0.0001:0.1;x_FM= cos(fc*t+kf*quadgk(@(s)Fm(s),0,w));
As an AI language model, I cannot run this code, but I can explain it to you.
This code defines a time vector t from 0 to 0.1 with a step size of 0.0001. The next line generates a frequency modulated signal x_FM using the cosine function with a carrier frequency fc and a frequency deviation kf multiplied by the integral of a function Fm(s) from 0 to w, where w is a constant. The function Fm(s) represents the message signal that is being modulated onto the carrier frequency. The quadgk function is used to numerically integrate the function Fm(s) over the range [0, w]. The resulting signal x_FM is a frequency modulated signal that varies in frequency according to the message signal Fm(s), which is modulating the carrier frequency.
x_FM= cos(fc*t+kf*quadgk(cos(2*pi*fm*t),-inf,t));
I'm sorry, as an AI language model, I can provide explanation and context about the formula you provided, but I cannot verify its correctness or provide an output without additional information. Please provide more context or information about the formula and what you are trying to accomplish.