enormUC: Expectiles of the Normal Distribution

Description Usage Arguments Details Value Author(s) See Also Examples

Description

Density function, distribution function, and expectile function and random generation for the distribution associated with the expectiles of a normal distribution.

Usage

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denorm(x, mean = 0, sd = 1, log = FALSE)
penorm(q, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE)
qenorm(p, mean = 0, sd = 1, Maxit.nr = 10, Tol.nr = 1.0e-6,
       lower.tail = TRUE, log.p = FALSE)
renorm(n, mean = 0, sd = 1)

Arguments

x, p, q

See deunif.

n, mean, sd, log

See rnorm.

lower.tail, log.p

Same meaning as in pnorm or qnorm.

Maxit.nr, Tol.nr

See deunif.

Details

General details are given in deunif including a note regarding the terminology used. Here, norm corresponds to the distribution of interest, F, and enorm corresponds to G. The addition of “e” is for the ‘other’ distribution associated with the parent distribution. Thus denorm is for g, penorm is for G, qenorm is for the inverse of G, renorm generates random variates from g.

For qenorm the Newton-Raphson algorithm is used to solve for y satisfying p = G(y). Numerical problems may occur when values of p are very close to 0 or 1.

Value

denorm(x) gives the density function g(x). penorm(q) gives the distribution function G(q). qenorm(p) gives the expectile function: the value y such that G(y)=p. renorm(n) gives n random variates from G.

Author(s)

T. W. Yee and Kai Huang

See Also

deunif, deexp, dnorm, amlnormal, lms.bcn.

Examples

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my.p <- 0.25; y <- rnorm(nn <- 1000)
(myexp <- qenorm(my.p))
sum(myexp - y[y <= myexp]) / sum(abs(myexp - y))  # Should be my.p

# Non-standard normal
mymean <- 1; mysd <- 2
yy <- rnorm(nn, mymean, mysd)
(myexp <- qenorm(my.p, mymean, mysd))
sum(myexp - yy[yy <= myexp]) / sum(abs(myexp - yy))  # Should be my.p
penorm(-Inf, mymean, mysd)      #  Should be 0
penorm( Inf, mymean, mysd)      #  Should be 1
penorm(mean(yy), mymean, mysd)  #  Should be 0.5
abs(qenorm(0.5, mymean, mysd) - mean(yy))  #  Should be 0
abs(penorm(myexp, mymean, mysd) - my.p)    #  Should be 0
integrate(f = denorm, lower = -Inf, upper = Inf,
          mymean, mysd)  #  Should be 1

## Not run: 
par(mfrow = c(2, 1))
yy <- seq(-3, 3, len = nn)
plot(yy, denorm(yy), type = "l", col="blue", xlab = "y", ylab = "g(y)",
     main = "g(y) for N(0,1); dotted green is f(y) = dnorm(y)")
lines(yy, dnorm(yy), col = "darkgreen", lty = "dotted", lwd = 2)  # 'original'

plot(yy, penorm(yy), type = "l", col = "blue", ylim = 0:1,
     xlab = "y", ylab = "G(y)", main = "G(y) for N(0,1)")
abline(v = 0, h = 0.5, col = "red", lty = "dashed")
lines(yy, pnorm(yy), col = "darkgreen", lty = "dotted", lwd = 2) 
## End(Not run)

VGAM documentation built on Jan. 16, 2021, 5:21 p.m.