| stpm-package | Stochastic Process Model for Analysis of Longitudinal and Time-to-Event Outcomes | 
| assign_to_global | function loading results in global environment | 
| ex_data | This is the longitudinal genetic dataset. | 
| func1 | An internal function to compute m and gamma based on continuous-time model (Yashin et. al., 2007) | 
| get.column.index | An internal function to obtain column index by its name | 
| getNextY.cont | An internal function to compute next Y based on continous-time model (Yashin et. al., 2007) | 
| getNextY.cont2 | An internal function to compute next value of physiological variable Y | 
| getNextY.discr | An internal function to compute the next value of physiological variable Y based on discrete-time model (Akushevich et. al., 2005) | 
| getNextY.discr.m | An internal function to compute next m based on dicrete-time model | 
| getPrevY.discr | An internal function to compute previous value of physiological variable Y based on discrete-time model | 
| getPrevY.discr.m | An internal function to compute previous m based on discrete-time model | 
| longdat | This is the longitudinal dataset. | 
| LRTest | Likelihood-ratio test | 
| m | An internal function to compute m from | 
| make.short.format | An internal function which construct short data format from a given long | 
| mu | An internal function to compute mu | 
| prepare_data | Data pre-processing for analysis with stochastic process model methodology. | 
| prepare_data_cont | Prepares continuouts-time dataset. | 
| prepare_data_discr | Prepares discrete-time dataset. | 
| sigma_sq | An internal function to compute sigma square analytically | 
| simdata_cont | Multi-dimensional simulation function for continuous-time SPM. | 
| simdata_discr | Multi-dimension simulation function | 
| simdata_gamma_frailty | This script simulates data using familial frailty model. We use the following variation: gamma(mu, ssq), where mu is the mean and ssq is sigma square. See: https://www.rocscience.com/help/swedge/webhelp/swedge/Gamma_Distribution.htm | 
| simdata_time_dep | Simulation function for continuous trait with time-dependant coefficients. | 
| sim_pobs | Multi-dimension simulation function for data with partially observed covariates (multidimensional GenSPM) with arbitrary intervals | 
| spm | A central function that estimates Stochastic Process Model parameters a from given dataset. | 
| spm.impute | Multiple Data Imputation with SPM | 
| spm_continuous | Continuous multi-dimensional optimization | 
| spm_cont_lin | Continuous multi-dimensional optimization with linear terms in mu only | 
| spm_cont_quad_lin | Continuous multi-dimensional optimization with quadratic and linear terms | 
| spm_con_1d | Fitting a 1-D SPM model with constant parameters | 
| spm_con_1d_g | Fitting a 1-D genetic SPM model with constant parameters | 
| spm_discrete | Discrete multi-dimensional optimization | 
| spm_pobs | Continuous-time multi-dimensional optimization for SPM with partially observed covariates (multidimensional GenSPM) | 
| spm_projection | A data projection with previously estimated or user-defined parameters. Projections are constructed for a cohort with fixed or normally distributed initial covariates. | 
| spm_time_dep | A function for the model with time-dependent model parameters. | 
| stpm | Stochastic Process Model for Analysis of Longitudinal and Time-to-Event Outcomes | 
| trim | Returns string w/o leading or trailing whitespace | 
| trim.leading | Returns string w/o leading whitespace | 
| trim.trailing | Returns string w/o trailing whitespace | 
| vitstat | Vital (mortality) statistics. |