
Optimizing Pareto Distribution proposal
srpareto_optimize.RdThe srpareto_optimize() function generates an optimized proposal for a targeted Pareto Distribution.
The proposal can be customized and adjusted based on various options provided by the user.
Usage
srpareto_optimize(
scale = NULL,
shape = NULL,
xl = NULL,
xr = NULL,
steps = 4091,
proposal_range = NULL,
theta = 0.1,
target_sample_size = 1000,
verbose = FALSE
)Arguments
- scale
(optional) Numeric. scale parameter of the Pareto Distribution. Defaults to
NULL, which implies a scalable proposal withscale = 1.- shape
(optional) Numeric. shape parameter of the Pareto Distribution. Defaults to
NULL, which implies a scalable proposal withshape = 1.- xl
Numeric. Left truncation bound for the target distribution. Defaults to
-Inf, representing no left truncation.- xr
Numeric. Right truncation bound for the target distribution. Defaults to
Inf, representing no right truncation.- steps
(optional) Integer. Desired number of steps in the proposal. Defaults to
NULL, which means the number of steps is determined automatically during optimization.- proposal_range
(optional) Numeric vector. Specifies the range for optimizing the steps part of the proposal. Defaults to
NULL, indicating automatic range selection.- theta
Numeric. A parameter for proposal optimization. Defaults to 0.1.
- target_sample_size
(optional) Integer. Target sample size for proposal optimization. Defaults to
1000.- verbose
Boolean. If
TRUE, detailed optimization information, including areas and steps, will be displayed. Defaults toFALSE.
Value
The user does not need to store the returned value, because the package internally cashes the proposal. However, we explain here the full returned proposal for advanced users.
A list containing the optimized proposal and related parameters for the specified built-in distribution: #'
dataDetailed information about the proposal steps, including
x,s_upper,p_a, ands_upper_lower.areasThe areas under the left tail, steps, and right tail of the proposal distribution.
steps_numberThe number of steps in the proposal.
f_paramsThe parameters (
scaleandshape) of the Beta distribution.
Details
When srpareto_optimize() is explicitly called:
A proposal is created and cached. If no parameters are provided, a standard proposal is created with
rate = 1.Providing
ratecreates a custom proposal, which is cached for use withsrpareto_custom().The optimization process can be controlled via parameters such as
steps,proposal_range, ortheta. If no parameters are provided, the proposal is optimized via brute force based on the.target_sample_size.
See also
srpareto_custom: Function to sample from a custom proposal tailored to user specifications.