erfinv(0.25)

ans = 0.2253

For inputs outside[1],erfinvreturnsNaN. For-1and1,erfinvreturns-InfandInf, respectively.

erfinv([-2 -1 1 2])

ans =NaN -Inf Inf NaN

Find the inverse error function of the elements of a matrix.

M = [0 -0.5; 0.9 -0.2]; erfinv(M)

ans =0 -0.4769 1.1631 -0.1791

Plot the inverse error function for -1 < x < 1.

x = -1:0.01:1; y = erfinv(x); plot(x,y) gridonxlabel('x') ylabel('erfinv(x)') title('Inverse Error Function for -1 < x < 1')

Generate Gaussian distributed random numbers using uniformly distributed random numbers. To convert a uniformly distributed random numberto a Gaussian distributed random number, use the transform

Note that becausexhas the form-1 + 2*rand(1,10000), you can improve accuracy by using误差补函数invinstead oferfinv. For details, seeTips.

Generate 10,000 uniformly distributed random numbers on the interval[1]. Transform them into Gaussian distributed random numbers. Show that the numbers follow the form of the Gaussian distribution using a histogram plot.

rng('default') x = -1 + 2*rand(1,10000); y = sqrt(2)*erfinv(x); h = histogram(y);