Normal_sym_trunc_ab | R Documentation |
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.
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,
...
)
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. |
The normal symmetric truncated distribution is a special case of the trucated normal distribution.
See Normal_trunc_ab
.
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.
Haizhen Wu and A. Jonathan R. Godfrey.
ExtDist for other standard distributions.
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