Density, distribution, quantile, random number
generation and parameter estimation functions for the symmetric truncated normal distribution with parameters, sigma,
a and b which represent the lower and upper truncation points respectively.
Parameter estimation can be based on a weighted or unweighted i.i.d sample and can be carried out numerically.
Usage
dNormal_sym_trunc_ab(x, sigma = 0.3, a = 0, b = 1, params = list(sigma,
a, b), ...)
pNormal_sym_trunc_ab(q, sigma = 0.3, a = 0, b = 1, params = list(mu = 2,
sigma = 5, a = 0, b = 1), ...)
qNormal_sym_trunc_ab(p, sigma = 0.3, a = 0, b = 1, params = list(mu = 2,
sigma = 5, a = 0, b = 1), ...)
rNormal_sym_trunc_ab(n, mu = 2, sigma = 3, a = 0, b = 1,
params = list(sigma, a, b), ...)
eNormal_sym_trunc_ab(X, w, method = "numerical.MLE", ...)
lNormal_sym_trunc_ab(X, w, mu = 2, sigma = 3, a = 0, b = 1,
params = list(sigma, a, b), logL = TRUE, ...)
Arguments
x,q
A vector of quantiles.
a,b
Boundary parameters.
params
A list that includes all named parameters.
...
Additional parameters
p
A vector of probabilities.
n
Number of observations.
mu,sigma
Shape parameters.
X
Sample observations.
w
An optional vector of sample weights.
method
Parameter estimation method.
logL
logical;if TRUE, lNormal_sym_trunc_ab gives the log-likelihood, otherwise the likelihood is given.
Details
The normal symmetric truncated distribution is a special case of the trucated normal distribution.
See Normal_trunc_ab.
Value
dNormal_sym_trunc_ab gives the density, pNormal_sym_trunc_ab the distribution function,
qNormal_sym_trunc_ab the quantile function, rNormal_sym_trunc_ab generates random deviates,and
eNormal_sym_trunc_ab estimates the parameters. lNormal_sym_trunc_ab provides the log-likelihood function.