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