### All plots generated by Monolix can be exported

All plots generated by Monolix can be exported as a figure or as text files in order to be able to plot it in another way or with other software for more flexibility.

All the files can be exported in R for example using the following command

read.table("/path/to/file.txt", sep = ",", comment.char = "", header = T)

Remarks

- The separator is the one defined in the user preferences. We set “,” in this example as it is the one by default.
- The command
`comment.char = ""`is needed for some files because to define groups or color, we use the character # that can be interpreted as a comment character by R.

The list of plots below corresponds to all the plots that Monolix can generate. They are computed with the task “Plots”, and the list of plots to compute can be selected by clicking on the button next to the task as shown below, prior to running the task.

Exporting the charts data can be made through the Export menu or through the preferences as described here.

In the following, we describe all the files generated by the export function

- Charts concerning the Data (Observed data).
- Charts concerning the model for the observations (Individual fits, Observations vs predictions, Scatter plot of the residuals, Distribution of the residuals
- Charts concerning the model for the individual parameters (Distribution of the individual parameters, Distribution of the random effects, Correlation between random effects, Individual parameters vs covariates)
- Charts concerning the predictive checks and predictions (Visual predictive checks, Numerical predictive checks, BLQ predictive checks, Prediction distribution)
- Charts concerning the convergence diagnosis (SAEM, MCMC) and the tasks results (Standard errors for the estimates)

## Charts concerning the Data

### Observed data (continuous, categorical, and count)

*xxx_observations.txt*

*xxx_observations.txt*

Description: observation values

### Full output file description

Column |
Description |
Comment |

id | Subject identifier | – |

OCC | Occasion value | (optional) if there is IOV in the data set |

time | Observation time | – |

y | Observation value (loq) | The name of the column is the observation name |

censored | 1 if the observation is censored, 0 otherwise | – |

split | Name of the split the subject belongs to | – |

color | Name of the color the observation is colored with | – |

filter | 1 if the subject is filtered, 0 otherwise | – |

### Observed data (event)

*xxx_curves.txt*

*xxx_curves.txt*

Description: observation values

### Full output file description

Column |
Description |
Needed Task |

time | Observation times | – |

survivalFunction | Survival of first event | – |

averageEventNumber | Average number of event at that time | – |

split | Name of the split the subject occasion belongs to | – |

*xxx_censored.txt*

*xxx_censored.txt*

Description: censored values

### Full output file description

Column |
Description |
Needed Task |

time | Observation times | – |

values | Survival of first event | – |

split | Name of the split the subject occasion belongs to | – |

## Model for the observations

### Individual Fits

*xxx_observations.txt*

*xxx_observations.txt*

Description: observation values

### Full output file description

Column |
Description |
Comment |

id | Subject identifier | – |

OCC | Occasion value | (optional) if there is IOV in the data set |

time | Observation time | – |

y | Observation value (loq) | – |

median | Prediction interval median | – |

piLower | Lower percentile of the individual prediction interval | – |

piUpper | Upper percentile of the individual prediction interval | – |

censored | 1 if the observation is censored, 0 otherwise | – |

*xxx_fits.txt*

*xxx_fits.txt*

Description: individual fits based on population parameters and individual parameters

### Full output file description

Column |
Description |
Needed Task |

id | Subject identifier | – |

OCC | Occasion value | (optional) if there is IOV in the data set |

time | Continuous time grid used to compute fits | – |

pop | Prediction using population parameter values and average covariate value from the population (continuous) or reference covariate value (categorical). | – |

popPred | Prediction using population parameter values and individual covariates. | – |

indivPredMean | Prediction based on the individual parameter values estimated by conditional mean | Conditional distribution need to be computed |

indivPredMode | Prediction based on the individual parameter values estimated by conditional mode | EBEs need to be computed |

### Observation vs Prediction

*xxx_obsVsPred.txt*

*xxx_obsVsPred.txt*

Description: observation and prediction (pop & indiv) values

### Full output file description

Column |
Description |
Needed Task |

id | Subject identifier | – |

OCC | Occasion value | (optional) if there is IOV in the data set |

time | time of the observation | |

y | Observation value (loq) | – |

y_simBlq | Observation value (simulated blq) | |

popPred | Predictions based on population parameter values | |

indivPredMean | Predictions based on the individual parameter values estimated by conditional mean | Conditional distribution need to be computed |

indivPredMode | Predictions based on the individual parameter values estimated by conditional mode | EBEs need to be computed |

censored | 1 if the observation is censored, 0 otherwise | |

split | Name of the split the subject occasion belongs to | |

color | Name of the color the observation is colored with | |

filter | 1 if the subject is filtered, 0 otherwise | – |

*xxx_obsVsSimulatedPred.txt*

*xxx_obsVsSimulatedPred.txt*

Description: observation and simulated prediction values

### Full output file description

Column |
Description |
Needed Task |

rep | Replicate id | |

id | Subject identifier | – |

OCC | Occasion value | (optional) if there is IOV in the data set |

time | time of the observation | |

y | Observation value (loq) | – |

y_simBlq | Observation value (simulated blq) | |

indivPredSimulated | Predictions based on the simulated individual parameter values estimated by conditional distribution | Conditional distribution need to be computed |

censored | 1 if the observation is censored, 0 otherwise | |

split | Name of the split the subject occasion belongs to | |

color | Name of the color the observation is colored with | |

filter | 1 if the subject is filtered, 0 otherwise |

*xxx_visualGuides.txt*

*xxx_visualGuides.txt*

Description: splines and confidence intervals for predictions

### Full output file description

Column |
Description |
Needed Task |

popPred | Continuous grid over population prediction values | – |

popPred_spline | Spline ordinates for population predictions | – |

popPred_piLower | Lower percentile of prediction interval for population predictions | – |

popPred_piUpper | Upper percentile of prediction interval for population predictions | – |

indivPred | Continuous grid over individual prediction values | – |

indivPred_spline | Spline ordinates for individual predictions | – |

indivPred_piLower | Lower percentile of prediction interval for individual predictions | – |

indivPred_piUpper | Upper percentile of prediction interval for individual predictions | – |

split | Name of the split the visual guides belong to |

### Distribution of the residuals

*xxx_pdf.txt*

*xxx_pdf.txt*

Description: probability density function of each residual type (pwres, iwres, npde)

### Full output file description

Column |
Description |
Needed Task |

pwRes_abscissa | Abscissa for pwres pdf | – |

pwRes_pdf | Pdf of pwres | – |

iwRes_abscissa | Abscissa for iwres pdf | – |

iwRes_pdf | Pdf of the iwres | – |

npde_abscissa | Abscissa for npde pdf | – |

npde_pdf | Pdf of the npde | – |

split | – |

*xxx_cdf.txt*

*xxx_cdf.txt*

Description: cumulative distribution function of each residual type (pwres, iwres, npde)

### Full output file description

Column |
Description |
Needed Task |

pwRes_abscissa | Abscissa for pwres cdf | – |

pwRes_cdf | Cdf of pwres | – |

iwRes_abscissa | Abscissa for iwres cdf | – |

iwRes_cdf | Cdf of the iwres | – |

npde_abscissa | Abscissa for npde cdf | – |

npde_cdf | Cdf of the npde | – |

split | – |

*theoreticalGuides.txt*

*theoreticalGuides.txt*

Description: theoretical guides for the pdf and the cdf

### Full output file description

Column |
Description |
Needed Task |

abscissa,pdf,cdf | Abscissa for the theoretical curves | – |

Theoretical value of the pdf | – | |

cdf | Theoretical value of the cdf | – |

### Scatter plot of the residuals

*xxx_prediction_percentiles_iwRes.txt*

*xxx_prediction_percentiles_iwRes.txt*

Description: prediction percentiles of the iwREs to plot iwRes w.r.t. the prediction. The same files exists with the pwres and the npde.

### Full output file description

Column |
Description |
Needed Task |

prediction | Value of the prediction | – |

empirical_median | Empirical median of the iwRes | – |

empirical_lower | Empirical lower percentile of the iwRes | |

empirical_upper | Empirical upper percentile of the iwRes | |

theoretical_median | Theoretical median of the iwRes | |

theoretical_lower | Theoretical lower of the iwRes | |

theoretical_upper | Theoretical upper of the iwRes | |

theoretical_median_piLower | Lower bound of the theoretical median prediction interval | |

theoretical_median_piUpper | Upper bound of the theoretical median prediction interval | |

theoretical_lower_piLower | Lower bound of the theoretical lower prediction interval | |

theoretical_lower_piUpper | Upper bound of the theoretical lower prediction interval | |

theoretical_upper_piLower | Lower bound of the theoretical upper prediction interval | |

theoretical_upper_piUpper | Upper bound of the theoretical upper prediction interval | |

split | Name of the split the subject occasion belongs to |

*xxx_time_percentiles_iwRes.txt*

*xxx_time_percentiles_iwRes.txt*

Description: time percentiles of the iwREs to plot iwRes w.r.t. the time. The same files exists with the pwres and the npde.

### Full output file description

Column |
Description |
Needed Task |

time | Value of the time | – |

empirical_median | Empirical median of the iwRes | – |

empirical_lower | Empirical lower percentile of the iwRes | |

empirical_upper | Empirical upper percentile of the iwRes | |

theoretical_median | Theoretical median of the iwRes | |

theoretical_lower | Theoretical lower of the iwRes | |

theoretical_upper | Theoretical upper of the iwRes | |

theoretical_median_piLower | Lower bound of the theoretical median prediction interval | |

theoretical_median_piUpper | Upper bound of the theoretical median prediction interval | |

theoretical_lower_piLower | Lower bound of the theoretical lower prediction interval | |

theoretical_lower_piUpper | Upper bound of the theoretical lower prediction interval | |

theoretical_upper_piLower | Lower bound of the theoretical upper prediction interval | |

theoretical_upper_piUpper | Upper bound of the theoretical upper prediction interval | |

split | Name of the split the subject occasion belongs to |

*xxx_residuals.txt*

*xxx_residuals.txt*

Description: residuals values (pwres, iwres, npde)

### Full output file description

Column |
Description |
Needed Task |

id | Subject identifier | – |

OCC | Occasion value | (optional) if there is IOV in the data set |

time | Observation times | – |

prediction_pwRes | Predictions based on population parameter values | SAEM |

pwRes | PwRes (computed with observations) | SAEM |

pwRes_blq | PwRes (computed with simulated blq) | |

prediction_iwRes_mean | Predictions based on the individual parameter values estimated by conditional mean (INDIVESTIM) if available, SAEM either | |

iwRes_mean | IwRes (computed with observations and individual parameter values estimated by conditional mean (INDIVESTIM) if available, SAEM either) | |

iwRes_mean_simBlq | IwRes (computed with simulated blq and individual parameter values estimated by conditional mean (INDIVESTIM) if available, SAEM either) | |

prediction_iwRes_mode | Predictions based on the individual parameter values estimated by conditional mode (INDIVESTIM) | |

iwRes_mode | IwRes (computed with observations and the individual parameter values estimated by conditional mode (INDIVESTIM)) | |

iwRes_mean_simBlq | IwRes (computed with simulated blq and the individual parameter values estimated by conditional mode (INDIVESTIM)) | |

prediction_npde | Predictions based on population parameter values | |

npde | Npde (computed with observations) | |

npde_simBlq | Npde (computed with simulated blq) | SAEM – If there are some censored data in the data set |

censored | 1 if the observation is censored, 0 otherwise | |

split | Name of the split the subject occasion belongs to | |

color | Name of the color the observation is colored with | |

filter | 1 if the subject is filtered, 0 otherwise | – |

*xxx_simulatedResiduals.txt*

*xxx_simulatedResiduals.txt*

Description: simulated residuals values

### Full output file description

Column |
Description |
Needed Task |

rep | replicate | – |

id | Subject identifier | – |

OCC | Occasion value | (optional) if there is IOV in the data set |

time | Observation times | – |

prediction_iwRes | Predictions based on the simulated individual parameter values based on the conditional distribution | |

iwRes_simulated | IwRes (computed with observations and the simulated individual parameter values) | |

iwRes_simulated_simBlq | IwRes (computed with simulated blq and the simulated individual parameter values) | |

censored | 1 if the observation is censored, 0 otherwise | – |

split | Name of the split the subject occasion belongs to | |

color | Name of the color the observation is colored with | |

filter | 1 if the subject is filtered, 0 otherwise | – |

*xxx_spline.txt*

*xxx_spline.txt*

Description: splines (residuals values against time and prediction)

### Full output file description

Column |
Description |
Needed Task |

time_pwRes | Time grid for pwRes spline | SAEM |

time_pwRes_spline | pwRes against time spline | SAEM |

time_iwRes | Time grid for iwRes spline | At least SAEM |

time_iwRes_spline | iwRes against time spline | At least SAEM |

time_npde | Time grid for npde spline | SAEM |

time_npde_spline | npde against time spline | SAEM |

prediction_pwRes | Prediction grid for pwRes spline | SAEM |

prediction_pwRes_spline | pwRes against population prediction spline | SAEM |

prediction_iwRes | Prediction grid for iwRes spline | At least SAEM |

prediction_iwRes_spline | iwRes against individual prediction spline | At least SAEM |

prediction_npde | Prediction grid for npde spline | SAEM |

prediction_npde_npde | npde against population prediction spline | SAEM |

split | Name of the split the visual guides belong to | If the chart is splitted |

*xxx_{time,population,individual}Bins.txt*

*xxx_{time,population,individual}Bins.txt*

Description: bins values for the corresponding axis.

### Full output file description

Column |
Description |
Needed Task |

binsValues | Abscissa bins values | – |

split | Name of the split the bins refer to | If the chart is splitted |

## Model for the individual parameters

### Distribution of the individual parameters

*cdf.txt*

*cdf.txt*

### Full output file description

Column |
Description |
Needed Task |

param_abscissa | Abscissa of the cdf of the individual parameter param | – |

param_cdf | Empirical cdf of the individual parameter param | – |

split | Name of the split the subject occasion belongs to |

*pdf.txt*

*pdf.txt*

### Full output file description

Column |
Description |
Needed Task |

param_abscissa | Abscissa of the pdf of the individual parameter param | – |

param_pdf | Empirical pdf of the individual parameter param | – |

split | Name of the split the subject occasion belongs to |

*visualGuides.txt*

*visualGuides.txt*

### Full output file description

Column |
Description |
Needed Task |

param_abscissa | Abscissa of the pdf and the pdf of the individual parameter param | – |

param_pdf | Theoretical pdf of the individual parameter param | – |

param_cdf | Theoretical cdf of the individual parameter param |

### Distribution of the random effects

*cdf.txt*

*cdf.txt*

### Full output file description

Column |
Description |
Needed Task |

param_abscissa | Abscissa of the cdf of the standardized random effect of param | – |

param_cdf | Empirical cdf of the standardized random effect of param | – |

split | Name of the split the subject occasion belongs to |

*pdf.txt*

*pdf.txt*

### Full output file description

Column |
Description |
Needed Task |

param_abscissa | Abscissa of the pdf of the standardized random effect of param | – |

param_pdf | Empirical pdf of the standardized random effect of param | – |

split | Name of the split the subject occasion belongs to |

*StandardizedEta.txt*

*StandardizedEta.txt*

Description: standardized random effects of the individual parameters

### Full output file description

Column |
Description |
Needed Task |

id | Subject identifier | – |

OCC | Occasion value | (optional) if there is IOV in the data set |

standEta_X_method | Standardized random effects values on each individual parameter with variability.
It can be StandEta_SAEM, StandEta_Mean, StandEta_Mode |
– |

filter | 1 if the subject is filtered, 0 otherwise | – |

*SimulatedStandardizedEta.txt*

*SimulatedStandardizedEta.txt*

Description: simulated standardized random effects of the individual parameters

### Full output file description

Column |
Description |
Needed Task |

rep | Replicate id | – |

id | Subject identifier | – |

OCC | Occasion value | (optional) if there is IOV in the data set |

standEta_X_simulated | Standardized random effects values on each individual parameter with variability. | – |

filter | 1 if the subject is filtered, 0 otherwise | – |

### Correlation between Random Effects

*eta.txt*

*eta.txt*

Description: standard error on individual parameter predictions

### Full output file description

Column |
Description |
Needed Task |

id | Subject identifier | – |

OCC | Occasion value | (optional) if there is IOV in the data set |

eta_X_method | Random effects values on each individual parameter with variability. It can be
eta_SAEM, eta_Mean, or eta_Mode |
– |

color | Name of the color the ID is colored with | – |

filter | 1 if the subject is filtered, 0 otherwise | – |

*simulatedEta.txt*

*simulatedEta.txt*

Description: standard error on individual parameter predictions

### Full output file description

Column |
Description |
Needed Task |

rep | Replicate number | |

id | Subject identifier | – |

OCC | Occasion value | (optional) if there is IOV in the data set |

eta_X_simulated | Simulated random effects values on each individual parameter | – |

color | Name of the color the ID is colored with | – |

filter | 1 if the subject is filtered, 0 otherwise | – |

*visualGuides.txt*

*visualGuides.txt*

Description: spline and linear regression for each couple of individual parameters plotted one against the other

This is done for each combination of parameter p1 and p2 to have p1 w.r.t. p2

### Full output file description

Column |
Description |
Needed Task |

p1_vs_p2_abscissa | Abscissa | – |

p1_vs_p2_spline | Spline ordinates | – |

p1_vs_p2_regression | Linear regression ordinates | – |

### Individual Parameters Vs Covariates

*covariates.txt*

*covariates.txt*

Description: individual parameters and random effects and covariate value for each subject

### Full output file description

Column |
Description |
Needed Task |

id | Subject identifier | – |

OCC | Occasion value | (optional) if there is IOV in the data set |

trans_X_method | Individual parameter value in the transformed space. It can be X_SAEM, X_mean, or X_mode | – |

eta_X_method | Random effects values. It can be eta_X_SAEM, eta_Mean, or eta_Mode | – |

covariate | Covariates values | |

split | ||

color | Name of the color the observation is colored with | |

filter | 1 if the subject is filtered, 0 otherwise |

*simulatedCovariates.txt*

*simulatedCovariates.txt*

Description: simulated individual parameters and random effects and covariate value for each subject

### Full output file description

Column |
Description |
Needed Task |

rep | Replicate of the simulation | |

id | Subject identifier | – |

OCC | Occasion value | (optional) if there is IOV in the data set |

trans_X_simulated | Simulated transformed individual parameter value. | – |

eta_X_simulated | Simulated random effects values. | – |

covariate | Covariates values | |

split | ||

color | Name of the color the observation is colored with | |

filter | 1 if the subject is filtered, 0 otherwise | – |

*visualGuides.txt*

*visualGuides.txt*

Description: spline and linear regression for each couple of individual parameters plotted against a covariate

This is done for each combination of parameter *param* and covariate *cov* to have *param* w.r.t. *cov*

### Full output file description

Column |
Description |
Needed Task |

param_vs_cov_abscissa | Abscissa | – |

param_vs_cov_spline | Spline ordinates | – |

param_vs_cov_regression | Linear regression ordinates | – |

## Predictive checks and prediction

### Visual Predictive Checks (continuous)

*xxx_observations.txt*

*xxx_observations.txt*

Description: observation values

### Full output file description

Column |
Description |
Needed Task |

id | Subject identifier | – |

OCC | Occasion value | (optional) if there is IOV in the data set |

time | Observation times | – |

y | Observation values (loq) | – |

y_simBlq | Observation values (simulated blq) | |

censored | 1 if the observation is censored, 0 otherwise | – |

split | Name of the split the subject occasion belongs to | |

color | Name of the color the observation is colored with | |

filter | 1 if the subject is filtered, 0 otherwise | – |

*xxx_bins.txt*

*xxx_bins.txt*

Description: bins values for the corresponding axis.

### Full output file description

Column |
Description |
Needed Task |

binsValues | Abscissa bins values | – |

split | Name of the split the bins refer to | If the chart is splitted |

*xxx_percentiles.txt*

*xxx_percentiles.txt*

Description: empirical and theoretical percentiles values (lower, median & upper) + confidence interval on theoretical percentiles (lower & upper)

### Full output file description

Column |
Description |
Needed Task |

bins_middles | Abscissa bin middles | – |

empirical_median | Empirical median | – |

empirical_lowerPercentile | Empirical lower percentile | – |

empirical_upperPercentile | Empirical upper percentile | – |

theoretical_median | Theoretical median | – |

theoretical_median_piLower | Lower percentile of prediction interval of theoretical median | – |

theoretical_median_piUpper | Upper percentile of prediction interval of theoretical median | – |

theoretical_lowerPercentile | Median of the prediction interval for the lower percentile | – |

theoretical_lower_piLower | Lower percentile of the prediction interval for the lower percentile | – |

theoretical_lower_piUpper | Upper percentile of the prediction interval for the lower percentile | – |

theoretical_upperPercentile | median of the prediction interval for the upper percentile | – |

theoretical_upper_piLower | Lower percentile of the prediction interval for the upper percentile | – |

theoretical_upper_piUpper | Upper percentile of the prediction interval for the upper percentile | – |

split | Name of the split the visual guides belong to | If the chart is splitted |

### Visual Predictive Checks (discrete)

*xxx_distribution.txt*

*xxx_distribution.txt*

Description: discrete observation modalities theoretical distribution (among continuous time grid)

### Full output file description

Column |
Description |
Needed Task |

binsTimeBefore | Abscissa bins time value before this time | – |

binsTimeAfter | Abscissa bins time value after this time | |

propCategory_empirical | Empirical proportion of the modality set represented by the subchart | – |

propCategory_median | Median of the prediction interval for the proportion of the modality set represented by the subchart | – |

propCategory_piLower | Lower percentile of the prediction interval for proportion of the modality set represented by the subchart | – |

propCategory_piUpper | Upper percentile of the prediction interval for proportion of the modality set represented by the subchart | – |

category | Label for modality sets | |

split | Name of the split the distributions refer to | – |

*xxx_xBins.txt*

*xxx_xBins.txt*

Description: bins values for the x-axis.

### Full output file description

Column |
Description |
Needed Task |

binsValues | Abscissa bins values | – |

split | Name of the split the bins refer to | If the chart is splitted |

### Visual Predictive Checks (event)

*xxx_curves.txt*

*xxx_curves.txt*

Description: observation values

### Full output file description

Column |
Description |
Needed Task |

time | Observation times | – |

survivalFunction_empirical | Empirical survival of first event | – |

survivalFunction_median | Survival median | |

survivalFunction_pXX | Survival percentile XX | |

averageEventNumber_empirical | Empirical mean number of events | – |

averageEventNumber_median | Median mean number of events | |

averageEventNumber_pXX | Percentile XX mean number of events | |

split | Name of the split the subject occasion belongs to | If the chart is splitted |

*xxx_censored.txt*

*xxx_censored.txt*

Description: censored values

### Full output file description

Column |
Description |
Needed Task |

time | Observation times | – |

values | Survival of first event | – |

split | Name of the split the subject occasion belongs to | – |

### BLQ Predictive Checks

*xxx_cumulatedBLQfrequencies.txt*

*xxx_cumulatedBLQfrequencies.txt*

Description: censored simulated observations cumulated frequency

### Full output file description

Column |
Description |
Needed Task |

time | Time | – |

empiricalCumulatedFrequencies | Empirical fraction of data that is BLQ between time 0 and time t | – |

median | Prediction interval median | – |

piLower | Lower bound of prediction interval | – |

piUpper | Upper bound of prediction interval | – |

split | Name of the split the visual guides belong to |

### Numerical Predictive Check

*xxx_cdf.txt*

*xxx_cdf.txt*

Description: empirical and theoretical cumulative distribution function of observations

### Full output file description

Column |
Description |
Needed Task |

time | Cdf continuous grid time | – |

empiricalCdf | Empirical cdf based on observations | – |

theoreticalCdf | Median of prediction interval for cdf | – |

piLower | Lower percentile of prediction interval for cdf | – |

piUpper | Upper percentile of prediction interval for cdf | – |

split | Name of the split the visual guides belong to |

### Prediction distribution (continuous)

*xxx_observations.txt*

*xxx_observations.txt*

Description: observation values

### Full output file description

Column |
Description |
Needed Task |

id | Subject identifier | – |

OCC | Occasion value | (optional) if there is IOV in the data set |

time | Observation times | – |

y | Observation values (loq) | – |

censored | 1 if the observation is censored, 0 otherwise | – |

split | Name of the split the subject occasion belongs to | |

color | Name of the color the observation is colored with | |

filter | 1 if the subject occasion is filtered, 0 otherwise |

*xxx_percentiles.txt*

*xxx_percentiles.txt*

Description: theoretical percentiles computed on continuous grid

### Full output file description

Column |
Description |
Needed Task |

time | Continuous time grid used for simulation | – |

median | Median | – |

pPercentile | Percentile | – |

split | Name of the split the visual guides belong to | If the chart is splitted |

### Prediction distribution (discrete)

*xxx_distribution.txt*

*xxx_distribution.txt*

Description: discrete observation modalities theoretical distribution (among continuous time grid)

### Full output file description

Column |
Description |
Needed Task |

binsTimeBefore | Abscissa bins time value before this time | – |

binsTimeAfter | Abscissa bins time value after this time | |

propCategory_empirical | Empirical proportion of the modality set represented by the subchart | – |

propCategory_median | Median of the prediction interval for the proportion of the modality set represented by the subchart | – |

propCategory_piLower | Lower percentile of the prediction interval for proportion of the modality set represented by the subchart | – |

propCategory_piUpper | Upper percentile of the prediction interval for proportion of the modality set represented by the subchart | – |

category | Label for modality sets | |

split | Name of the split the distributions refer to | – |

*xxx_xBins.txt*

*xxx_xBins.txt*

Description: bins values for the x-axis.

### Full output file description

Column |
Description |
Needed Task |

binsValues | Abscissa bins values | – |

split | Name of the split the bins refer to | If the chart is splitted |

## Convergence diagnosis

### SAEM

*CvParam.txt*

*CvParam.txt*

Description: evolution of the parameters during SAEM iterations

### Full output file description

Column |
Description |
Needed Task |

iteration | Iteration number | – |

convergenceIndicator | Convergence Indicator | – |

phase | 1 for exploratory and 2 for smoothing | |

X | Parameter X | – |

### MCMC

*convergences.txt*

*convergences.txt*

Description: evolution of the convergence with respect to the MCMC iterations

### Full output file description

Column |
Description |
Needed Task |

iteration | Iteration number | – |

E_X | Conditional expectation of the parameter X | – |

sd_X | Conditional standard error of the parameter X |

*bounds.txt*

*bounds.txt*

Description: bounds for each parameter corresponding to the bounds on the graph. The first line corresponds to the minimum and the second one corresponds to the maximum.

### Full output file description

Column |
Description |
Needed Task |

E_X | Conditional expectation of the parameter X | – |

sd_X | Conditional standard error of the parameter X |

### Standard errors of the estimates

*rse.txt*

*rse.txt*

Description: Standards errors for each parameter

### Full output file description

Column |
Description |
Needed Task |

X | parameter | – |

rse_lin | Relative standard error with linearization method | – |

rse_sa | Relative standard error with linearization method |