Generalized Score Matching Estimators

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Documentation for package ‘genscore’ version 1.0.2.2

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AUC Calculates the AUC of an ROC curve.
avgrocs Takes the vertical average of ROC curves.
beautify_rule Replaces consecutive "&"s and "|"s in a string to a single & and |.
binarySearch_bin Finds the index of the bin a number belongs to using binary search.
calc_crit Calculates penalized or unpenalized loss in K and eta given arbitrary data
check_endpoints Checks if two equally sized numeric vectors satisfy the requirements for being left and right endpoints of a domain defined as a union of intervals.
compare_two_results Compares two lists returned from estimate().
compare_two_sub_results Compares two lists returned from get_results().
cov_cons Random generator of inverse covariance matrices.
crbound_mu The Cram\'er-Rao lower bound (times 'n') for estimating the mean parameter from a univariate truncated normal sample with known variance parameter.
crbound_sigma The Cram\'er-Rao lower bound (times 'n') for estimating the variance parameter from a univariate truncated normal sample with known mean parameter.
diff_lists Computes the sum of absolute differences between two lists.
diff_vecs Computes the sum of absolute differences in the finite non-NA/NULL elements between two vectors.
domain_for_C Returns a list to be passed to C that represents the domain.
eBIC eBIC score with or without refitting.
estimate The main function for the generalized score-matching estimator for graphical models.
find_max_ind Finds the max index in a vector that does not exceed a target number.
frac_pow Evaluate x^(a/b) and |x|^(a/b) with integer a and b with extension to conventional operations.
gcd Finds the greatest (positive) common divisor of two integers.
gen Random data generator from general 'a'-'b' distributions with general domain types, assuming a and b are rational numbers.
get_crit_nopenalty Minimized loss for unpenalized restricted asymmetric models.
get_dist Finds the distance of each element in a matrix x to the its boundary of the domain while fixing the others in the same row.
get_elts The function wrapper to get the elements necessary for calculations for all settings.
get_elts_ab The R implementation to get the elements necessary for calculations for general a and b.
get_elts_exp The R implementation to get the elements necessary for calculations for the exponential square-root setting (a=0.5, b=0.5).
get_elts_gamma The R implementation to get the elements necessary for calculations for the gamma setting (a=0.5, b=0).
get_elts_gauss The R implementation to get the elements necessary for calculations for the gaussian setting on R^p.
get_elts_loglog The R implementation to get the elements necessary for calculations for the log-log setting (a=0, b=0).
get_elts_loglog_simplex The R implementation to get the elements necessary for calculations for the log-log setting (a=0, b=0) on the p-simplex.
get_elts_trun_gauss The R implementation to get the elements necessary for calculations for the gaussian setting (a=1, b=1) on domains other than R^p.
get_g0 Calculates the l2 distance to the boundary of the domain and its gradient for some domains.
get_g0_ada Adaptively truncates the l2 distance to the boundary of the domain and its gradient for some domains.
get_h_hp Generator of h and hp (derivative of h) functions.
get_h_hp_adaptive Generator of adaptive h and hp (derivative of h) functions.
get_h_hp_vector Generator of h and hp (derivative of h) functions.
get_postfix_rule Changes a logical expression in infix notation to postfix notation using the shunting-yard algorithm.
get_results Estimate K and eta using elts from 'get_elts()' given one lambda_K (and lambda_eta if non-profiled non-centered) and applying warm-start with strong screening rules.
get_safe_log_h_hp Asymptotic log of 'h' and 'hp' functions for large 'x' for modes with an unbounded 'h'.
get_trun The truncation point for 'h' for 'h' that is truncated (bounded but not naturally bounded).
h_of_dist Finds the distance of each element in a matrix x to the its boundary of the domain while fixing the others in the same row (dist(x, domain)), and calculates element-wise h(dist(x, domain)) and h\'(dist(x, domain)) (w.r.t. each element in x).
interval_intersection Finds the intersection between two unions of intervals.
interval_union Finds the union between two unions of intervals.
in_bound Returns whether a vector or each row of a matrix falls inside a domain.
lambda_max Analytic solution for the minimum lambda_K that gives the empty graph.
makecoprime Makes two integers coprime.
make_domain Creates a list of elements that defines the domain for a multivariate distribution.
make_folds Helper function for making fold IDs for cross validation.
mu_sigmasqhat Estimates the mu and sigma squared parameters from a univariate truncated normal sample.
naiveSearch_bin Finds the index of the bin a number belongs to using naive search.
parse_ab Parses an ab setting into rational numbers a and b.
parse_ineq Parses an ineq expression into a list of elements that represents the ineq.
random_init_polynomial Randomly generate an initial point in the domain defined by a single polynomial with no negative coefficient.
random_init_simplex Generates a random point in the (p-1)-simplex.
random_init_uniform Generates random numbers from a finite union of intervals.
ran_mat Random generator of matrices with given eigenvalues.
read_exponent Parses the exponent part into power_numer and power_denom.
read_exponential Parses the integer coefficient in an exponential term.
read_one_term Parses the first term of a non-uniform expression.
read_uniform_term Attempts to parse a single term in x into power_numer and power_denom.
refit Loss for a refitted (restricted) unpenalized model
rexp_truncated Generates translated and truncated exponential variables.
rlaplace_truncated Generates laplace variables truncated to a finite union of intervals.
rlaplace_truncated_centered Generates centered laplace variables with scale 1.
search_bin Finds the index of the bin a number belongs to.
s_at Returns the character at a position of a string.
s_output Helper function for outputting if verbose.
test_lambda_bounds Searches for a tight bound for lambda_K that gives the empty or complete graph starting from a given lambda with a given step size
test_lambda_bounds2 Searches for a tight bound for lambda_K that gives the empty or complete graph starting from a given lambda
tp_fp Calculates the true and false positive rates given the estimated and true edges.
update_finite_infinity_for_uniform Maximum between finite_infinity and 10 times the max abs value of finite elements in 'lefts' and 'rights'.
varhat Asymptotic variance (times 'n') of the estimator for 'mu' or 'sigmasq' for the univariate normal on a general domain assuming the other parameter is known.