# inst/unitTests/runitmodeLogitnorm.R In logitnorm: Functions for the Logitnormal Distribution

```#TODO

.setUp <-function () {
}

.tearDown <- function () {
}

test.rightMode <- function(){
theta0 <- c(mu=1.5, sigma=0.8)
#plot the true and the rediscovered distributions
xGrid = seq(0,1, length.out=81)[-c(1,81)]
dx <- dlogitnorm(xGrid, mu=theta0[1], sigma=theta0[2])
plot( dx~xGrid, type="l")

mle <- modeLogitnorm(mu=theta0[1], sigma=theta0[2] )
abline(v=mle,col="gray")

#check by monte carlo integration
#z <- rlogitnorm(1e6, mu=theta0[1], sigma=theta0[2]);	var(z)
#dz <- density(z)
#checkEqualsNumeric( dz\$x[which.max(dz\$y)], mle, tolerance=5e-2)
checkEqualsNumeric( 0.88, mle, tolerance=1e-2)
}

test.leftMode <- function(){
theta0 <- c(mu=-1.5, sigma=0.8)
#plot the true and the rediscovered distributions
xGrid = seq(0,1, length.out=81)[-c(1,81)]
dx <- dlogitnorm(xGrid, mu=theta0[1], sigma=theta0[2])
plot( dx~xGrid, type="l")

mle <- modeLogitnorm(mu=theta0[1], sigma=theta0[2] )
abline(v=mle,col="gray")

#check by monte carlo integration
# deprecated: did not run on Windows
#z <- rlogitnorm(1e6, mu=theta0[1], sigma=theta0[2]);	var(z)
#dz <- density(z)
#checkEqualsNumeric( dz\$x[which.max(dz\$y)], mle, tolerance=5e-2)
checkEqualsNumeric( 0.12, mle, tolerance=1e-2)		# regression 0.12 calculated previously
}
```

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logitnorm documentation built on May 31, 2017, 4:45 a.m.