| AFROC | AF*ROC* curve (alternative free-response *ROC* curve) |
| AFROC_curve | FROC curve as an embedding map |
| argMax | Arg Max: Extract a subscript corresponding component is a max |
| argMin | Arg Min: Extract a subscript corresponding component is a... |
| array_easy_example | Example array |
| array_of_hit_and_false_alarms_from_vector | Array of hits and false alarms; 2019 Jun 18 |
| Author_vs_classic_for_AUC | validation of AUC calculation |
| BayesianFROC | Theory of FROC Analysis via Bayesian Approaches |
| caseID_m_q_c_vector_from_NI_M_Q_C | Creats vectors: 'm,q,c' from integers: 'M,Q,C' |
| check_hit_is_less_than_NL | Chech total hit is less than NL for each reader and each... |
| check_rhat | Diagnosis of MCMC sampling |
| chi_square_at_replicated_data_and_MCMC_samples_MRMC | chi square at replicated data drawn (only one time) from... |
| chi_square_goodness_of_fit | _*Chi square goodness of fit statistics*_ at each MCMC sample... |
| chi_square_goodness_of_fit_from_input_all_param | Calculates the Goodness of Fit (Chi Square) |
| chi_square_goodness_of_fit_from_input_all_param_MRMC | Chi square in the case of MRMC at a given dataset and a given... |
| Chi_square_goodness_of_fit_in_case_of_MRMC_Posterior_Mean | Chi square statistic (goodness of fit) in the case of MRMC at... |
| clearWorkspace | Clear Work Space |
| Close_all_graphic_devices | Close the Graphic Device |
| color_message | message with colored item |
| compare | model comparison |
| comparison | model comparison |
| compile_all_models_in_pkg_BayesianFROC | Compile all stanfiles in pkg BayesianFROC |
| ConfirmConvergence | Check R hat criterion |
| Confirm_hit_rates_are_correctly_made_in_case_of_MRMC | Check whether each hit-rate is defined correctly |
| CoronaVirus_Disease_2019 | Who should be inspected? |
| CoronaVirus_Disease_2019_prevalence | Who should be inspected? |
| create_dataList_MRMC | Creates a _Single_ Dataset in Case of MRMC |
| create_dataset | Creates a dataset |
| Credible_Interval_for_curve | Draw FROC curves which means credible interval. |
| d | Data: A Single Reader and A Single Modality |
| dark_theme | Dark Theme |
| data_2modaities_2readers_3confidence | data: 2 readers, 2 modalities and 3 confideneces |
| data.bad.fit | Data: Single reader and Single modality |
| data_generate_NaN_in_fit_with_iteration1111_seed1234 | *NaN in samplings* A Single Reader and A Single Modality |
| data.hier.ficitious | Multiple reader and Multiple modality data |
| dataList.Chakra.1 | Data: A Single Reader and A Single Modality |
| dataList.Chakra.1.with.explantation | Data: A Single Reader and A Single Modality |
| dataList.Chakra.2 | Data: A Single Reader and A Single Modality |
| dataList.Chakra.3 | Data: A Single Reader and A Single Modality |
| dataList.Chakra.4 | Data: A Single Reader and A Single Modality |
| dataList.Chakra.Web | An FROC Data of Multiple-Reader and Multiple-Modality |
| dataList.Chakra.Web.orderd | An FROC Data of Multiple-Reader and Multiple-Modality |
| dataList.divergent.transition.in.case.of.srsc | An FROC Dataset with *_Divergent Transitions_* in case of A... |
| dataList.High | Data: Single reader and Single modality |
| dataList.high.ability | Data: A Single Reader and A Single Modality |
| dataList.Low | Data: Single reader and Single modality |
| dataList.low.ability | Data: A Single Reader and A Single Modality |
| dataList.one.modality | dataset of Multiple reader and one modality |
| data_low_p_value | *low p-value = 0.012* Data: Single reader and Single modality |
| data_much_low_p_value | *low p-value = 0.002* A Single Reader and A Single Modality |
| data.MultiReaderMultiModality | Multiple reader and Multiple modality data |
| data.nonconverge.srsc | *Non-Convergent* Data: Single reader and Single modality |
| data_of_36_readers_and_a_single_modality | 36 readers and a sinle modality data |
| dataset_creator_by_specifying_only_M_Q | Creates dataset |
| dataset_creator_for_many_Readers | create data for MRMC |
| dataset_creator_new_version | Create a Dataset (version 2) Interactively |
| data.SingleReaderSingleModality | Data: A Single Reader and A Single Modality |
| dcasewise | An casewised FROC Data of Multiple-Reader and... |
| dd | Multiple Reader and Multiple Modality Data |
| ddd | Multiple reader and Multiple modality data |
| dddd | One reader and Multiple modality data |
| ddddd | Data of MRMC; Model * _ does _* converge. |
| dddddd | Multiple reader and single modality data |
| ddddddd | Multiple reader and 2 modalities data such that all... |
| dd.orderd | Multiple Reader and Multiple Modality Data |
| demo_Bayesian_FROC | demonstration |
| demo_Bayesian_FROC_without_pause | demonstration without pausing |
| Draw_an_area_of_AUC_for_srsc | Draw a Region of the area under the AFROC curve |
| Draw_a_prior_sample | Draw One Sample from Prior |
| Draw_a_simulated_data_set | Draw a simulated dataset from model distributions with... |
| Draw_a_simulated_data_set_and_Draw_posterior_samples | Draw a dataset and MCMC samples |
| Draw_AUC | Draw the Region of AUC of AFROC |
| draw.CFP.CTP.from.dataList | Plot the pairs of CFPs and CTPs |
| DrawCurves | Draw FROC curves |
| DrawCurves_MRMC | Draw the FROC curves for all modalities and readers |
| DrawCurves_MRMC_pairwise | Draw the FROC curves with Colour |
| DrawCurves_MRMC_pairwise_BlackWhite | Draw the FROC curves without colour |
| DrawCurves_MRMC_pairwise_col | Draw the FROC curves with Colour |
| DrawCurves_srsc | Draw the FROC curves |
| draw_latent_noise_distribution | Visualization of the Latent Gaussian for false rates |
| draw_latent_signal_distribution | Visualization of Latent Gaussians ( Signal Distribution) |
| draw_ROC_Curve | Title |
| draw_ROC_Curve_from_fitted_model | Title |
| dz | Threshold: parameter of an MRMC model |
| Empirical_FROC_via_ggplot | Empirical FROC curve via ggplot2 |
| error_message | Error Message for Data Format |
| error_message_on_imaging_device_rhat_values | Error message *on a plot plane* (imaging device) |
| error_MRMC | Comparison of Estimates and Truth in case of MRMC |
| error_srsc | Validation via replicated datasets from a model at a given... |
| error_srsc_error_visualization | Visualization for Error of Estimator |
| error_srsc_variance_visualization | Visualization Of variance Analysis |
| explanation_about_package_BayesianFROC | Explanation of this package |
| explanation_for_what_curves_are_drawn | Print out about what curves are drawn |
| extractAUC | Extract AUC |
| extract_data_frame_from_dataList_MRMC | Extract sub data frame from list of FROC data |
| extract_data_frame_from_dataList_srsc | extract data frame from datalist in case of srsc |
| extract_EAP_by_array | Extract Etimates Preserving Array Format. |
| extract_EAP_CI | Extracts Estimates as vectors from stanfit objects |
| extract_estimates_MRMC | MRMC: Extract All Posterior Mean Estimates from... |
| extract_parameters_from_replicated_models | Extract Estimates From Replicated MRMC Model |
| false_and_its_rate_creator | False Alarm Creator for both cases of MRMC and srsc |
| false_and_its_rate_creator_MRMC | MRMC: False Alarm Creator For each Modality and each Reader. |
| fffaaabbb | Package Development tools and memo. |
| file_remove | Execute before submission to delete redandunt files. |
| fit_a_model_to | Fit a model to data |
| fit_Bayesian_FROC | Fit a model to data |
| fit_GUI | Fit with GUI via Shiny |
| fit_GUI_dashboard | Fit with GUI via Shiny (Simple version) |
| fit_GUI_MRMC | Fit with GUI via Shiny in case of MRMC |
| fit_GUI_MRMC_new | Fit an MRMC model to data with Shiny GUI |
| fit_GUI_ROC | Fit (very bad, MCMC not converge) ROC model with GUI via... |
| fit_GUI_Shiny | Fit a model with GUI of Shiny |
| fit_GUI_Shiny_MRMC | Fit with GUI via Shiny (in case of MRMC) |
| fit_GUI_simple_from_apppp_file | Fit with GUI via Shiny |
| fit_MRMC | Fit and Draw the FROC models (curves) |
| fit_MRMC_casewise | Fit and Draw the FROC models (curves) |
| fit_MRMC_versionTWO | Fit and Draw the FROC models (curves) version2. |
| fit_Null_hypothesis_model_to_ | Fit the null model |
| fit_srsc | fit a model to data in the case of A Single reader and A... |
| fit_srsc_ROC | fit a model to data in the case of A Single reader and A... |
| flatnames | from rstan package |
| flat_one_par | Makes array names |
| foo | without double quote |
| fooo | taboo or |
| foo_of_a_List_of_Arrays | Apply functions by each Array in a list |
| FROC_curve | FROC curve as an embedding map |
| from_array_to_vector | Transform from an * _array_* to a * _vector_* |
| get_posterior_variance | Alternative of 'rstan::get_posterior_mean()' |
| get_samples_from_Posterior_Predictive_distribution | Synthesizes Samples from Predictive Posterior Distributions... |
| get_treedepth_threshold | get treedepth threshold |
| ggplotFROC | Draw FROC curves by two parameters a and b |
| ggplotFROC.EAP | Draw FROC curves by two parameters a and b |
| give_name_srsc_CFP_CTP_vector | Give a Name For CTP CFP vector |
| give_name_srsc_data | Give a name for srsc data list component |
| grapes-greater-than-greater-than-grapes | Fit a model |
| hit_generator_from_multinomial | Under Const |
| hit_rate_adjusted_from_the_vector_p | hit rate adjusted from a vector p |
| hits_creator_from_rate | MRMC Dataset Creator From Hit Rate. |
| hits_false_alarms_creator_from_thresholds | Hits and False Alarms Creator |
| hits_from_thresholds | MRMC Hit Creator from thresholds, mean and S.D. |
| hits_rate_creator | MRMC Hit Rates Creator from Thresholds, Mean and S.D. |
| horizontal_from_vertical_in_each_case | Transfer From Vertical placement into Horizontal placement... |
| initial_values_specification_for_stan_in_case_of_MRMC | Initial values for HMC (Hamiltonian Moncte Carlo Markov... |
| install_imports | Installer. |
| inv_Phi | Inverse function of the Cumulative distribution function... |
| is_length_zero | Is argument of length zero ? |
| is_logical_0 | is.logical(0) |
| is_na_in_vector | Detect NA in a vector |
| is_na_list | Check whether a list contains NA or not. |
| is_stanfitExtended | Check whether class is _stanfitExtended_ for any R object |
| make_TeX | Make a TeX file for summary |
| make_true_parameter_MRMC | Make a true model parameter and include it in this package |
| metadata_srsc_per_image | Create metadata for MRMC data. |
| metadata_to_DrawCurve_MRMC | Create metadata for MRMC data |
| metadata_to_fit_MRMC | Create metadata for MRMC data |
| metadata_to_fit_MRMC_casewise | Create metadata for MRMC data |
| m_q_c_vector_from_M_Q_C | Creats vectors: 'm,q,c' from integers: 'M,Q,C' |
| mu | Mean of signal: parameter of an MRMC model |
| mu_truth | Mean of signal: parameter of an MRMC model |
| mu_truth_creator_for_many_readers_MRMC_data | mu of MRMC model paramter |
| name_of_param_whose_Rhat_is_maximal | Extract a name of parameter from StanfitExtended object (or... |
| names_argMax | Extract name from a real vector whose component is the... |
| p | Hit Rate: parameter of an MRMC model |
| pairs_plot_if_divergent_transition_occurred | Pairs plot for divergent transition |
| pause | Pause for Demo |
| Phi | The Cumulative distribution function Phi(x) of the Standard... |
| Phi_inv | Inverse function of the Cumulative distribution function... |
| plot_curve_and_hit_rate_and_false_rate_simultaneously | Curve and signal distribution and noise d log Phi() for a... |
| plot_dataset_of_ppp | plot datasets using calculation of ppp |
| plot_dataset_of_ppp_MRMC | plot datasets using calculation of ppp |
| plot_empirical_FROC_curves | Plot empirical FROC Curves by traditional ways of 'ggplot2' |
| plot_FPF_and_TPF_from_a_dataset | Plot FPF and TPF from MRMC data |
| plot_FPF_TPF_via_dataframe_with_split_factor | Scatter Plot of FPFs and TPFs via Splitting Factor |
| plotFROC | Draw FROC curves by two parameters a and b |
| plot_ROC_empirical_curves | Empirical ROC curve |
| plot-stanfitExtended-missing-method | A generic function 'plot()' |
| plot_test | # Definition of a method for the inherited class... |
| pnorm_or_qnorm | pnorm or qnorm |
| print_minimal_reproducible_code_in_case_of_MRMC | Show minimal code in MRMC |
| print_stanfitExtended | Definition of a method for the inherited class... |
| print-stanfitExtended-method | A method for a generic function 'print()' for class... |
| prior_predictor | Predict some estimates of parameter |
| prior_print_MRMC | Print What Prior Are Used |
| prior_print_srsc | Print What Prior Are Used |
| priorResearch | Research for Prior |
| p_truth | Hit Rate: parameter of an MRMC model |
| p_value_of_the_Bayesian_sense_for_chi_square_goodness_of_fit | P value for goodness of fit : No longer used in 2019 Oct |
| rank_statistics_with_two_parameters | Rank Statistics |
| replicate_model_MRMC | Replicate Models |
| replicate_MRMC_dataList | MRMC: Replicates Datasets From Threshold, Mean and S.D. |
| R_hat_max | Max R hat |
| ROC_curve | Title |
| ROC_data_creator | Synthesize ROC data |
| ROC_data_creator2 | Synthesize ROC data |
| sbcc | SBC |
| seq_array_ind | Makes a Matrix from a vector of itegers |
| show_codes_in_my_manuscript | Show R codes used in my manuscript |
| showGM | the Graphical Model via PKG 'DiagrammeR' for the case of a... |
| Simulation_Based_Calibration_histogram | Draw a histogram of the rank statistics |
| Simulation_Based_Calibration_single_reader_single_modality_via_rstan_sbc | Simulation Based Calibration (SBC) for a single reader and a... |
| Simulation_Based_Calibration_via_rstan_sbc_MRMC | Simiulation Based Calibration (SBC) for a single reader and a... |
| size_of_return_value | Size of R object |
| small_margin | Margin |
| snippet_for_BayesianFROC | Edit Snippet |
| sortAUC | Prints a Ranking for AUCs for MRMC Data |
| Stan_code_validation | stan code |
| stanfitExtended | 'stanfitExtended', an S4 class inherited from the S4 class... |
| stanfit_from_its_inherited_class | Chage S4 class to stanfit |
| stan_model_of_sbc | Creates an object of class stanfit of SBC |
| stan_trace_of_max_rhat | a trace plot for a paramter whose R hat is largest |
| StatisticForANOVA | Statistic for ANOVA |
| summarize_MRMC | Summarize the estimates for MRMC case |
| summary_EAP_CI_srsc | Summary |
| Test_Null_Hypothesis_that_all_modalities_are_same | Test the Null hypothesis that all modalities are same |
| the_row_number_of_logical_vector | Extract the row number from a logical vector |
| trace_Plot | Trace plot |
| TRUE.Counter.in.vector | Count 'TRUE' in a Vector whose components are all Logical R... |
| v | Standard Deviation: parameter of an MRMC model |
| validation.dataset_srsc | Errors of Estimator for any Given true parameter |
| validation.draw_srsc | Draw Curves for validation dataset |
| vertical_from_horizontal_in_each_case | Transfer From Horizontal placement into Vertical placement... |
| viewdata | Build a table of FROC data |
| viewdata_MRMC | View MRMC data |
| viewdata_MRMC_casewise | View MRMC data |
| viewdata_srsc | Build a table of data in the case of A Single reader and A... |
| v_truth | Standard Deviation: parameter of an MRMC model |
| v_truth_creator_for_many_readers_MRMC_data | v of MRMC model paramter |
| waic | WAIC Calculator |
| z | Threshold: parameter of an MRMC model |
| z_from_dz | Thresholds from its difference |
| z_truth | Threshold : parameter of an MRMC model |
