create_set: Create set of samples by sampling with LHS and then checking...
In JohnNay/sa: Sensitivity Analysis for Complex Computational Models

Description Usage Arguments Value Functions References Examples

create_set creates sample that stay within constraints.

create_set(input_values = NULL, input_names = NULL, sample_count,
  constraints, model_data, model_data_formula = NULL,
  add_model_data_col = FALSE, create_input_values = NULL)

create_sample(input_values, input_names, sample_count)

keep_satisfied(sampled, constrained)

`input_values`	List
`input_names`	Character vector
`sample_count`	Numeric vector length one.
`constraints`	Character vector that is either "none" of is using only variable names that are specified in the input_values List argument. This character vector is evaluated in an environment created for the sampled data on the variables, and its evaluation results in a Logical vector that that subsets sampled.
`model_data`	Optional data.frame with the data that was used to build the model. This is used if one wants to ensure that all parameters tested are in the convex hull of the data used to build the model that is now being analyzed. This uses the WhatIf package in the Suggest field of the eat description file.
`model_data_formula`	optional formula for WhatIf package.
`add_model_data_col`	optional Logical for whether to add col
`create_input_values`	Instead of the input_values and input_names args which lead the function to use LHS and create the samples that way you can provide a function to this arg that takes an arg for how many samples to create and returns a data.frame with that many rows of samples.
`sampled`	Output of create sample_sample
`constrained`	Logical vector

Returns a data.frame of samples.

Returns a data.frame of samples.

Returns a data.frame of samples thats the same or less rows as input.

create_sample: Create a sample.
keep_satisfied: Stay within constraints.

B. Beachkofski, R. Grandhi, in 43rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference (American Institute of Aeronautics; Astronautics, 2002; http://arc.aiaa.org/doi/abs/10.2514/6.2002-1274).

R. Carnell, Lhs Latin Hypercube Samples (2012), (available at http://cran.r-project.org/web/packages/lhs/index.html).

fake_constraints <- "param1 < 0.5 & param2 > 0.5"
fake_data <- data.frame(param1 = runif(100), param2 = runif(100))
fake_constraints <- with(fake_data, eval(parse(text=fake_constraints)))
keep_satisfied(fake_data, fake_constraints)