Prev Next

@(@\newcommand{\B}[1]{ {\bf #1} } \newcommand{\R}[1]{ {\rm #1} } \newcommand{\W}[1]{ \; #1 \; }@)@This is dismod_at-20221105 documentation: Here is a link to its current documentation .
User Examples and Tests

See Also
Run One Example
     user_speed.py
example.db
Examples With Explanation
More Examples

See Also
get_started

Run One Example
If you have built dismod_at and are in the directory dismod_at.git , you can run one of these examples with the command
   python3_executable example/user/name
 where python3_executable is the python3 program and name is the name of the example. The name of the example includes the .py extension at the end, but does not include user_ at the front.

user_speed.py
The user_speed.py example is an exception; see its syntax .

example.db
Each of these examples will create a corresponding database called
   build/example/user/example.db
 which can be inspected using any sqlite viewer; e.g., http://sqlitebrowser.org/ .

Examples With Explanation
user_age_avg_split.py Non-uniform Age Average Grid
user_average_integrand.py Using the Python average_integrand Utility
user_bilevel_random.py Example Fitting With Two Levels of Random Effects
user_bnd_mulcov.py Bounding Covariate Multipliers Absolute Data Effect
user_cascade.py Generating Priors For Next Level Down Node Tree
user_censor.py Fitting Data That Has Negative Values Censored
user_change_grid.py Remove an Age or Time From a Smoothing
user_compress.py Using Data Interval Compression
user_connection_file.py Example Using connection_file
user_const_value.py Constrain Omega Using const_value
user_continue_fit.py Continuing a Fit From Where it Left Off
user_covid_19.py Model The Covid-19 Epidemic
user_csv2db.py csv2db_command: Example and Test
user_data_density.py Fit With Outliers Using Data Density Command
user_data_sim.py Explanation of Simulated Data Table, data_sim
user_diabetes.py An Example / Speed Test Fitting Simulated Diabetes Data
user_fit_fixed_both.py Fit Fixed First Then Both
user_fit_meas_noise.py Group Measurement Noise Covariate Multipliers, Gamma
user_fit_random.py Fitting Just Random Effects
user_fit_sim.py Fitting Simulated Data Example
user_group_mulcov.py Using Group Covariate Multipliers
user_hes_fixed_math.py Check the Hessian of the Fixed Effects Objective
user_hes_random.py Check the Hessian of the Random Effects Objective
user_hold_out_1.py Using hold_out in Data, Subset Data, and Option Tables
user_hold_out_2.py hold_out Command: Balancing Sex Covariate Values
user_ill_condition.py An Ill Conditioned Example Where Re-Scaling is Helpful
user_jump_at_age.py Zero Rate Until a Jump at a Known Age
user_lasso_covariate.py Using Lasso on Covariate Multiplier
user_mulstd.py Estimating Smoothing Standard Deviation Multiplies
user_no_children.py Case with no Children; i.e., no Random Effects
user_one_function.py Fitting One Function of Two Variables
user_plot_curve.py Example Plotting Log-Scaled Values w.r.t Age and Time
user_plot_data_fit.py Example Plotting The Data and Its Fit
user_plot_rate_fit.py Example Plotting The Rates for a Fit
user_predict_fit.py Predict Average Integrand Using Results of a Fit
user_predict_mulcov.py Predict Covariate Multiplier Values
user_residual.py Weighted Residuals
user_sample_asy.py Sample from Asymptotic Distribution for Model Variables
user_sample_asy_sim.py Sampling From The Asymptotic Distribution for a Simulated Data Fit
user_sample_sim.py Sample Posterior Using Simulated Data
user_sim_log.py Simulating Data with Log Transformed Distribution
user_speed.py A Simulate Data Speed Test
user_subgroup_mulcov.py Example Fitting With Subgroup Covariate Multipliers
user_sum_residual.py Sum of Residuals at Optimal Estimate
user_system_command_prc.py Example Using system_command_prc
user_trace_init.py Using Initialization Trace Option
user_trapezoidal.py Using the Trapezoidal ODE Solver
user_warm_start.py Continuing a Fit Using Ipopt Warm Start
user_zsum_child_rate.py Constrain Sum of Child Rate Effect to Zero
user_zsum_mulcov_meas.py Constrain Sum of Subgroup Measurement Covariate Multipliers to Zero
user_zsum_mulcov_rate.py Constrain Sum of Subgroup Rate Covariate Multipliers to Zero

More Examples
user_metropolis.py Predict Average Integrand Using Results of a Fit
user_const_random.py Fitting With Non-Zero Constant Random Effects in Smoothing Grid
user_diff_constraint.py Fitting with Constraints on Differences in Age and Time
user_re_scale.py Case Where Re-Scaling is Useful
Input File: example/user/user.omh