Criticality Plot
Usage
plot_estimated_dose_curve_mx(
name,
est_doses,
fit_coeffs,
fit_var_cov_mat,
curve_type,
protracted_g_value = 1,
conf_int_curve = 0.95,
place
)Arguments
- name
the dose to plot.
- est_doses
List of dose estimations results.
- fit_coeffs
Fitting coefficients matrix.
- fit_var_cov_mat
Fitting variance-covariance matrix.
- curve_type
gamma or neutron.
- protracted_g_value
Protracted \(G(x)\) value.
- conf_int_curve
Confidence interval of the curve.
- place
UI, report or save. Where the plot will be displayed.
Examples
#The fitting RDS result from the fitting module is needed. Alternatively, manual data
#frames that match the structure of the RDS can be used:
fit_coeffs <- data.frame(
estimate = c(0.001280319, 0.021038724, 0.063032534),
std.error = c(0.0004714055, 0.0051576170, 0.0040073856),
statistic = c(2.715961, 4.079156, 15.729091),
p.value = c(6.608367e-03, 4.519949e-05, 9.557291e-56),
row.names = c("coeff_C", "coeff_alpha", "coeff_beta")
)
fit_var_cov_mat <- data.frame(
coeff_C = c(2.222231e-07, -9.949044e-07, 4.379944e-07),
coeff_alpha = c(-9.949044e-07, 2.660101e-05, -1.510494e-05),
coeff_beta = c(4.379944e-07, -1.510494e-05, 1.605914e-05),
row.names = c("coeff_C", "coeff_alpha", "coeff_beta")
)
est_doses <- list(
list(
gamma = c(est = 2.173586, lwr = 1.784314, upr = 2.562857),
neutron = c(est = 1.811322, lwr = 1.486929, upr = 2.135715),
total = c(est = 3.984907, lwr = 3.271243, upr = 4.698572)
)
)
#FUNCTION PLOT_ESTIMATED_DOSE_CURVE_MX
plot_estimated_dose_curve_mx(
name = "Sample1",
est_doses = est_doses[[1]],
fit_coeffs = as.matrix(fit_coeffs)[,1],
fit_var_cov_mat = as.matrix(fit_var_cov_mat),
curve_type = "gamma",
protracted_g_value = 1,
conf_int_curve = 0.95,
place = "UI")
