effCont-helper function

Helper functions for continuous effectiveness distributions

These are functions to help in the creation and use of continuous effectiveness distributions.

cap(x, xmin = 1e-06, xmax = 1 - xmin)

effContMean(qfun, abs.tol = 1e-06, subdivisions = 500)

effContVar(qfun, mu, abs.tol = 1e-06, subdivisions = 500)

effContTrunc(dfun, pfun, qfun, ...)

Arguments

• x: a sample of effectiveness scores.
• xmin: lowest value to cap scores.
• xmax: highest value to cap scores.
• qfun: a quantile function.
• abs.tol: absolute accuracy requested, passed to integrate.
• subdivisions: the maximum number of subintervals, passed to integrate.
• mu: the expected value of the distribution (see effContMean).
• dfun: a density function.
• pfun: a distribution function.
• ...: additional arguments passed to other functions, if any.

Returns

cap: the original vector, but censored.

effContMean: the estimate of the expected value.

effContVar: the estimate of the variance.

effContTrunc: a list with components:

td	the truncated density function.
tp	the truncated distribution function.
tq	the truncated quantile function.

Details

cap caps (censor) a variable from below and above.

effContMean computes the expected value of a distribution by numerical integration of the given quantile function.

effContVar computes the variance of a distribution by numerical integration of the given quantile function.

effContTrun computes the density, distribution and quantile functions of the distribution resulting from truncating a given distribution between 0 and 1.

Examples

cap(c(0, .5, 1))

effContMean(function(p) qnorm(p, mean = 4))
effContMean(function(p) qbeta(p, 1, 2))

effContVar(function(p) qnorm(p, mean = 2, sd = 4), 2)
effContVar(function(p) qbeta(p, 1, 2), 1/3)

tr <- effContTrunc(dnorm, pnorm, qnorm, mean = .8, sd = .3)
x01 <- seq(0, 1, .01)
plot(x01, tr$d(x01), type = "l")
plot(x01, tr$p(x01), type = "l")
plot(x01, tr$q(x01), type = "l")

See Also

eff.cont.