Package index • spdesign

All functions
`all_priors_and_levels_specified()`	Check whether all priors and attributes have specified levels
`any_duplicates()`	Check whether any priors or attributes are specified with a value more than once
`attribute_level_balance()`	Check whether we can achieve attribute level balance
`attribute_levels()`	Generic for getting the attributes and levels from the utility function
`attribute_names()`	Generic for getting the attribute names
`block()`	Block the design
`calculate_a_error()`	A-error
`calculate_c_error()`	C-error
`calculate_d_error()`	D-error
`calculate_efficiency()`	Calculate efficiency
`calculate_efficiency_criteria()`	Calculate efficiency criteria
`calculate_s_error()`	S-error
`clean_utility()`	Cleans the utility expression
`coef(<spdesign>)`	Generic for extracting the vector of priors
`contains_dummies()`	Check whether the utility function contains dummy coded variables
`cor()`	Correlation
`cycle()`	Cycling of attribute levels
`define_base_x_j()`	Define base x_j
`define_x_j()`	Define x_j
`derive_vcov()`	Derive the variance covariance matrix of the design
`derive_vcov_mnl()`	Derive the variance covariance matrix for the MNL model
`derive_vcov_rpl()`	Derive the variance covariance matrix for the RPL model
`digitize()`	Expand the sequence of integers
`.onAttach()`	Print package startup message
`dummy_names()`	Find the position of the dummy coded attributes
`evaluate_design_candidate()`	Evaluate the design candidate
`exclude()`	Exclude rows from the candidate set
`expand_attribute_levels()`	Expand the list of attributes and levels to the "wide" format
`extract_all_names()`	Extract all names
`extract_attribute_names()`	Extract attribute names
`extract_distribution()`	Extract distributions
`extract_level_occurrence()`	Extract the frequency of levels
`extract_named_values()`	Extracts the named values of the utility function
`extract_param_distribution()`	Extract the parameter distribution
`extract_param_names()`	Extract parameter names
`extract_prior_distribution()`	Extract the prior distribution
`extract_specified()`	Extract specified
`extract_unparsed_values()`	Extract unparsed named values of the utilitiy function
`extract_values()`	Extract the value argument(s)
`federov()`	Find a design using a modified Federov algorithm
`fits_lvl_occurrences()`	Test whether a design candidate fits the constraints imposed by the level occurrences
`full_factorial()`	Generate the full factorial
`generate_design()`	Generate an efficient experimental design
`generate_rsc_candidate()`	Generates a candidate for the RSC algorithm
`has_bayesian_prior()`	Tests whether the utility expression contains Bayesian priors
`has_random_parameter()`	Tests whether the utility expression contains random parameters
`is_balanced()`	Tests whether a utility function is balanced
`level_balance()`	Print level balance of your design
`lvl_occurrences()`	Attribute level occurrence lookup tables
`make_draws()`	Make random draws
`make_mlhs()`	Make Modified Latin Hypercube Draws
`make_pseudo_random()`	Make pseudo random draws
`make_scrambled_halton()`	Make scrambled Halton draws
`make_scrambled_sobol()`	Make scrambled sobol draws
`make_standard_halton()`	Wrapper for halton()
`make_standard_sobol()`	Make sobol draws
`min_lvl_occurrence()`	Find minimum level occurrences
`nlvls()`	Find the number of levels
`normal()` `normal_p()` `lognormal()` `lognormal_p()` `triangular()` `triangular_p()` `uniform()` `uniform_p()`	Evaluating a distribution
`occurrences()`	Extract or set attribute level occurrences
`prepare_priors()`	Prepare the list of priors
`print(<spdesign>)`	A generic function for printing an 'spdesign' object
`print_efficiency_criteria()`	Creates a printable version of the efficiency criteria
`print_initial_header()`	Prints the initial header for the table of results
`print_iteration_information()`	Prints iteration information
`priors()`	Generic for extracting the vector of priors
`probabilities()`	Calculate the probabilities of the design
`probabilities_mnl()`	Calculate the MNL probabilities
`radical_inverse()`	Compute the radical inverse
`random()`	Make a random design
`random_design_candidate()`	Create a random design_object candidate
`relabel()`	Relabeling of attribute levels
`remove_all_brackets()`	Removes all brackets
`remove_prior()`	Removes the parameter from the utility string
`remove_round_brackets()`	Remove round bracket
`remove_square_brackets()`	Remove square bracket
`remove_whitespace()`	Remove all white spaces
`rep_cols()`	Repeat columns
`rep_rows()`	Repeat rows
`rsc()`	Make a design candidate based on the rsc algorithm
`set_default_level_occurrence()`	Sets the default level occurrence in an attribute level balanced design
`set_default_options()`	Validate design opt
`shuffle()`	Shuffle the order of points in the unit interval.
`summary(<spdesign>)`	Create a summary of the experimental design
`swap()`	Swapping of attribute
`too_small()`	Check if the design is too small
`transform_distribution()`	Transform distribution
`transform_lognormal()`	Transform to the lognormal distribution
`transform_normal()`	Transform to the normal distribution
`transform_triangular()`	Transform to the triangular distribution
`transform_uniform()`	Transform to the uniform distribution
`update_utility()`	Update the utility function
`utility_formula()`	Create formulas from the utility functions
`vcov(<spdesign>)`	Extract the variance co-variance matrix

Reference

All functions