# CS代考程序代写 #Central and non-central chi-squared distributions.

#Central and non-central chi-squared distributions.
#Central chi-squared dist:
x <- seq(0, 20, .15) y <- dchisq(x, df=5, ncp=0) plot(x, y, xaxt="n", yaxt="n", type="l", lwd=2, ylab=substitute(f(x))) #Non-central chi-squared dist: x <- seq(0, 20, .15) y <- dchisq(x, df=5, ncp=3) points(x, y, xaxt="n", yaxt="n", type="l", lwd=2, col="blue", ylab=substitute(f(x))) #================================================= #================================================= #Central and non-central t distributions. #Central t dist: x <- seq(-10, 10, .05) y <- dt(x,4,, ncp=0) plot(x, y, xaxt="n", yaxt="n", type="l", lwd=2, ylab=substitute(f(x)), xlim=c(-20,20)) #Non-central t dist: x <- seq(-16, 20, .1) y <- dt(x, 4, ncp=2) points(x, y, xaxt="n", yaxt="n", type="l", lwd=2, col="blue", ylab=substitute(f(x))) #================================================= #================================================= #Central and non-central F distributions. #Central F dist: x <- seq(0, 10, .05) y <- df(x, df1=3,df2=5, ncp=0) plot(x, y, xaxt="n", yaxt="n", type="l", lwd=2, ylab=substitute(f(x))) #Non-central F dist: x <- seq(0, 10, .1) y <- df(x, df1=3,df2=5, ncp=3) points(x, y, xaxt="n", yaxt="n", type="l", lwd=2, col="blue", ylab=substitute(f(x)))