theta_values (DataFrame or tuple) –
If theta_values is a DataFrame, then it contains one column for each theta variable
and (optionally) an objective value column (‘obj’) and columns that contains
Boolean results from confidence interval tests (labeled using the alpha value).
Each row is a sample.
Theta variables can be computed from theta_est_bootstrap,
theta_est_leaveNout, and leaveNout_bootstrap_test.
The objective value can be computed using the likelihood_ratio_test.
Results from confidence interval tests can be computed using the
leaveNout_bootstrap_test, likelihood_ratio_test, and
confidence_region_test.
If theta_values is a tuple, then it contains a mean, covariance, and number
of samples (mean, cov, n) where mean is a dictionary or Series
(indexed by variable name), covariance is a DataFrame (indexed by
variable name, one column per variable name), and n is an integer.
The mean and covariance are used to create a multivariate normal
sample of n theta values. The covariance can be computed using
theta_est(calc_cov=True).
theta_star (dict or Series, optional) – Estimated value of theta. The dictionary or Series is indexed by variable name.
Theta_star is used to slice higher dimensional contour intervals in 2D
alpha (float, optional) – Confidence interval value, if an alpha value is given and the
distributions list is empty, the data will be filtered by True/False
values using the column name whose value equals alpha (see results from
leaveNout_bootstrap_test, likelihood_ratio_test, and
confidence_region_test)
distributions (list of strings, optional) – Statistical distribution used to define a confidence region,
options = ‘MVN’ for multivariate_normal, ‘KDE’ for gaussian_kde, and
‘Rect’ for rectangular.
Confidence interval is a 2D slice, using linear interpolation at theta_star.
axis_limits (dict, optional) – Axis limits in the format {variable: [min, max]}
title (string, optional) – Plot title
add_obj_contour (bool, optional) – Add a contour plot using the column ‘obj’ in theta_values.
Contour plot is a 2D slice, using linear interpolation at theta_star.
add_legend (bool, optional) – Add a legend to the plot
filename (string, optional) – Filename used to save the figure
seed (int, optional) – Random seed used to generate theta values if theta_values is a tuple.
If None, the seed is not set.