pdf.LogNormal: Evaluate the probability mass function of a LogNormal...

In distributions3: Probability Distributions as S3 Objects

Evaluate the probability mass function of a LogNormal distribution

Description

Please see the documentation of LogNormal() for some properties of the LogNormal distribution, as well as extensive examples showing to how calculate p-values and confidence intervals.

Usage

## S3 method for class 'LogNormal'
pdf(d, x, drop = TRUE, elementwise = NULL, ...)

## S3 method for class 'LogNormal'
log_pdf(d, x, drop = TRUE, elementwise = NULL, ...)

Arguments

d	A LogNormal object created by a call to LogNormal().
x	A vector of elements whose probabilities you would like to determine given the distribution d.
drop	logical. Should the result be simplified to a vector if possible?
elementwise	logical. Should each distribution in d be evaluated at all elements of x (elementwise = FALSE, yielding a matrix)? Or, if d and x have the same length, should the evaluation be done element by element (elementwise = TRUE, yielding a vector)? The default of NULL means that elementwise = TRUE is used if the lengths match and otherwise elementwise = FALSE is used.
...	Arguments to be passed to dlnorm. Unevaluated arguments will generate a warning to catch mispellings or other possible errors.

Value

In case of a single distribution object, either a numeric vector of length probs (if drop = TRUE, default) or a matrix with length(x) columns (if drop = FALSE). In case of a vectorized distribution object, a matrix with length(x) columns containing all possible combinations.

See Also

Other LogNormal distribution: cdf.LogNormal(), fit_mle.LogNormal(), quantile.LogNormal(), random.LogNormal()

Examples

set.seed(27)

X <- LogNormal(0.3, 2)
X

random(X, 10)

pdf(X, 2)
log_pdf(X, 2)

cdf(X, 4)
quantile(X, 0.7)

distributions3 documentation built on Sept. 7, 2022, 5:07 p.m.