Function reference • riskyr

Initialization Creating riskyr scenarios and corresponding parameter collections.
`FFTrees_riskyr()`	Convert from FFTrees to riskyr objects.
`plot(<riskyr>)`	Plot a riskyr scenario.
`print(<summary.riskyr>)`	Print summary information of a riskyr scenario.
`riskyr()`	Create a riskyr scenario.
`riskyr.guide()`	Opens the riskyr package guides
`summary(<riskyr>)`	Summarize a riskyr scenario.
`df_scenarios`	A collection of riskyr scenarios from various sources (as df).
`scenarios`	A collection of riskyr scenarios from various sources (as list).
`init_num()`	Initialize basic numeric variables.
`init_pal()`	Initialize basic color information.
`init_txt()`	Initialize basic text elements.
`num`	List current values of basic numeric variables.
`popu`	A table of cases (in the current population).
`read_popu()`	Read population data (from df) into a riskyr scenario (description).
`pal`	List current values of scenario color palette.
`pal_bw`	Alternative color palette for black-and-white (greyscale) graphs.
`pal_bwp`	Alternative color palette for black-and-white graphs (for printing purposes).
`pal_crisk`	Color palette for cumulative risk curve.
`pal_kn`	Alternative color palette for kn.
`pal_mbw`	Modern and reduced color palette (in green/blue/bw).
`pal_mod`	Modern color palette (in green/blue/orange).
`pal_org`	Original color palette.
`pal_rgb`	Alternative color palette for graphs (with RGB colors).
`pal_unikn`	Alternative color palette for unikn.
`pal_vir`	Alternative color palette using viridis colors.
`txt`	Basic text elements.
`txt_TF`	Alternative text labels (TP, FN, FP, TN).
`txt_org`	List of original values of text elements.
Visualization Functions for creating graphical representations of riskyr scenarios.
`plot(<box>)`	Plot a frequency box object.
`plot(<riskyr>)`	Plot a riskyr scenario.
`plot_area()`	Plot an area diagram of probabilities or frequencies.
`plot_bar()`	Plot bar charts of population frequencies.
`plot_crisk()`	Plot a cumulative risk curve.
`plot_curve()`	Plot curves of selected values (e.g., PPV or NPV) as a function of prevalence.
`plot_fnet()`	Plot frequency net diagram of frequencies and probabilities.
`plot_icons()`	Plot an icon array of a population.
`plot_mosaic()`	Plot a mosaic plot of population frequencies.
`plot_plane()`	Plot a plane of selected values (e.g., PPV or NPV) as a function of sensitivity and specificity.
`plot_prism()`	Plot prism diagram of frequencies and probabilities.
`plot_tab()`	Plot a 2 x 2 contingency table of population frequencies.
`plot_tree()`	Plot a tree diagram of frequencies and probabilities.
Probabilities Lists and objects representing probability information.
`prob`	List current probability information.
`prev`	The prevalence (baseline probability) of a condition.
`sens`	The sensitivity (or hit rate) of a decision process or diagnostic procedure.
`mirt`	The miss rate of a decision process or diagnostic procedure.
`spec`	The specificity of a decision process or diagnostic procedure.
`fart`	The false alarm rate (or false positive rate) of a decision process or diagnostic procedure.
`ppod`	The proportion (or baseline) of a positive decision (aka. bias).
`PPV`	The positive predictive value of a decision process or diagnostic procedure.
`NPV`	The negative predictive value of a decision process or diagnostic procedure.
`FDR`	The false detection rate of a decision process or diagnostic procedure.
`FOR`	The false omission rate (FOR) of a decision process or diagnostic procedure.
`acc`	Accuracy (acc) is the probability of a correct decision.
`accu`	A list containing current accuracy information.
`err`	Error rate (err) as the probability of an incorrect decision.
Frequencies Lists and objects representing frequencies (i.e., various subsets of a population).
`freq`	List current frequency information.
`N`	Number of individuals in the population.
`cond_false`	Number of individuals for which the condition is false.
`cond_true`	Number of individuals for which the condition is true.
`dec_cor`	Number of individuals for which the decision is correct.
`dec_err`	Number of individuals for which the decision is erroneous.
`dec_neg`	Number of individuals for which the decision is negative.
`dec_pos`	Number of individuals for which the decision is positive.
`hi`	Frequency of hits or true positives (TP).
`mi`	Frequency of misses or false negatives (FN).
`fa`	Frequency of false alarms or false positives (FP).
`cr`	Frequency of correct rejections or true negatives (TN).
Computation and conversion Computing parameters and translating between representational formats and data/descriptions.
`comp_FDR()`	Compute a decision's false detection rate (FDR) from probabilities.
`comp_FOR()`	Compute a decision's false omission rate (FOR) from probabilities.
`comp_NPV()`	Compute a decision's negative predictive value (NPV) from probabilities.
`comp_PPV()`	Compute a decision's positive predictive value (PPV) from probabilities.
`comp_acc()`	Compute overall accuracy (acc) from probabilities.
`comp_accu_freq()`	Compute accuracy metrics of current classification results.
`comp_accu_prob()`	Compute exact accuracy metrics based on probabilities.
`comp_comp_pair()`	Compute a probability's (missing) complement and return both.
`comp_complement()`	Compute a probability's complement probability.
`comp_complete_prob_set()`	Compute a complete set of probabilities from valid probability inputs.
`comp_err()`	Compute overall error rate (err) from probabilities.
`comp_fart()`	Compute a decision's false alarm rate from its specificity.
`comp_freq()`	Compute frequencies from (3 essential) probabilities.
`comp_freq_freq()`	Compute frequencies from (4 essential) frequencies.
`comp_freq_prob()`	Compute frequencies from (3 essential) probabilities.
`comp_min_N()`	Compute a suitable minimum population size value N.
`comp_mirt()`	Compute a decision's miss rate from its sensitivity.
`comp_popu()`	Compute a population table (data) from frequencies (description).
`comp_ppod()`	Compute the proportion of positive decisions (ppod) from probabilities.
`comp_prev()`	Compute the condition's prevalence (baseline probability) from frequencies.
`comp_prob()`	Compute probabilities from (3 essential) probabilities.
`comp_prob_freq()`	Compute probabilities from (4 essential) frequencies.
`comp_prob_prob()`	Compute probabilities from (3 essential) probabilities.
`comp_sens()`	Compute a decision's sensitivity from its miss rate.
`comp_spec()`	Compute a decision's specificity from its false alarm rate.
`read_popu()`	Read population data (from df) into a riskyr scenario (description).
`write_popu()`	Write a population table (data) from a riskyr scenario (description).
Datasets Data used in examples and illustrations.
`df_scenarios`	A collection of riskyr scenarios from various sources (as df).
`BRCA1`	Cumulative risk of breast cancer in women with the BRCA1 mutation.
`BRCA1_mam`	Cumulative risk of breast cancer in women with the BRCA1 mutation.
`BRCA1_ova`	Cumulative risk of ovarian cancer in women with the BRCA1 mutation.
`BRCA2`	Cumulative risk of breast cancer in women with the BRCA2 mutation.
`BRCA2_mam`	Cumulative risk of breast cancer in women with the BRCA2 mutation.
`BRCA2_ova`	Cumulative risk of ovarian cancer in women with the BRCA2 mutation.
`t_A`	Cumulative risk curve A (main/transfer task A).
`t_B`	Cumulative risk curve B (main/transfer task B).
`t_I`	Cumulative risk curve I (introductory task).
Validation and formatting Verifying and displaying representational formats.
`is_complement()`	Verify that two numbers are complements.
`is_extreme_prob_set()`	Verify that a set of probabilities describes an extreme case.
`is_freq()`	Verify that input is a frequency (positive integer value).
`is_integer()`	Test for inters (i.e., whole numbers).
`is_matrix()`	Verify a 2x2 matrix as a numeric contingency table.
`is_perc()`	Verify that input is a percentage (numeric value from 0 to 100).
`is_prob()`	Verify that input is a probability (numeric value from 0 to 1).
`is_suff_prob_set()`	Verify a sufficient set of probability inputs.
`is_valid_prob_pair()`	Verify that a pair of probability inputs can be a pair of complementary probabilities.
`is_valid_prob_set()`	Verify that a set of probability inputs is valid.
`is_valid_prob_triple()`	Verify that a triple of essential probability inputs is valid.
`as_pb()`	Display a percentage as a (numeric and rounded) probability.
`as_pc()`	Display a probability as a (numeric and rounded) percentage.
Extensions Extensions and links to other packages.
`FFTrees_riskyr()`	Convert from FFTrees to riskyr objects.

Reference

Initialization

Visualization

Probabilities

Frequencies

Computation and conversion

Datasets

Validation and formatting

Extensions