add_common_aes | Adds aesthetics to all plots to reduce code duplication |
beta_params | Calculate alpha and beta parameters of beta distribution. |
calc_evpi | Expected Value of Perfect Information (EVPI) |
calc_evppi | Estimation of the Expected Value of Partial Perfect... |
calc_evsi | Calculate Expected Value of Sample Information (EVSI) |
calc_exp_loss | Calculate the expected loss at a range of willingness-to-pay... |
calculate_icers | Calculate incremental cost-effectiveness ratios (ICERs) |
calculate_icers_psa | Calculate incremental cost-effectiveness ratios from a 'psa'... |
calculate_outcome | A function that is used to calculate all outcomes |
ceac | Cost-Effectiveness Acceptability Curve (CEAC) |
compute_icers | compute icers for non-dominated strategies |
create_dsa_oneway | Create one-way deterministic sensitivity analysis object |
create_dsa_twoway | Create one-way deterministic sensitivity analysis object |
create_sa | A generic sensitivity analysis object |
dirichlet_params | Calculate alpha parameters of Dirichlet distribution. |
example_psa | Sample PSA data for testing |
example_psa_obj | Sample PSA data for testing |
gamma_params | Calculate shape and scale (or rate) parameters of a gamma... |
gen_psa_samp | Generate PSA Sample |
hund_strat | Sample deterministic data for testing |
is_owsa | check that object is owsa object |
labfun | used to automatically label continuous scales |
lnorm_params | Calculate location and scale parameters of a log-normal... |
make_param_seq | make a parameter sequence |
make_psa_obj | Create a PSA object |
metamodel | Linear regression metamodeling |
mm_run_reg | Build formula and run linear regression for metamodel |
number_ticks | Number of ticks for 'ggplot2' plots |
offset_trans | transformation for owsa_tornado |
owsa | One-way sensitivity analysis |
owsa_opt_strat | plot the optimal strategy as the parameter values change |
owsa_tornado | Tornado plot of a one-way sensitivity analysis |
plot.ceac | Plot of Cost-Effectiveness Acceptability Curves (CEAC) |
plot.evpi | Plot of Expected Value of Perfect Information (EVPI) |
plot.evppi | Plot of Expected Value of Partial Perfect Information (EVPPI) |
plot.evsi | Plot of Expected Value of Sample Information (EVSI) |
plot.exp_loss | Plot of Expected Loss Curves (ELC) |
plot.icers | Plot of ICERs |
plot.owsa | Plot a sensitivity analysis |
plot.psa | Plot the psa object |
plot.twsa | Two-way sensitivity analysis plot |
predict_ga | Function to compute the preposterior for each of the basis... |
predict_matrix_tensor_smooth_ga | Predict matrix tensor smooth (GA) |
predict.metamodel | Predict from a one-way or two-way metamodel |
predict_smooth_ga | Function to compute the preposterior for each of the basis... |
print.metamodel | Print metamodel |
print.sa | print a psa object |
psa_cdiff | Sample PSA dataset |
rdirichlet | Random number generation for the Dirichlet distribution with... |
run_owsa_det | Run deterministic one-way sensitivity analysis (OWSA) |
run_psa | Calculate outcomes for a PSA using a user-defined function. |
run_twsa_det | Run deterministic two-way sensitivity analysis (TWSA) |
summary.ceac | Summarize a ceac |
summary.metamodel | Summary of metamodel |
summary.psa | summarize a psa object across all simulations |
twsa | Two-way sensitivity analysis using linear regression... |
wrapper_of_user_model | Wrapper function for owsa_det and twsa_det |
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