Man pages for samuel-watson/glmmr
Design and analysis for generalised linear mixed models in R
| add_one_mat | Efficiently calculates the inverse of a super-matrix |
| aic_mcml | Calculates the Akaike Information Criterion for the GLMM |
| bessel1 | Bessel covariance function |
| blockmat | Create block matrix |
| confint_search | Confidence interval search procedure |
| Covariance | R6 Class representing a covariance function and data |
| cross_df | Generate crossed block structure |
| cycles | Generates all the orderings of a |
| Design | A GLMM Design |
| DesignSpace | A GLMM Design Space |
| d_lik_optim | Optimises the log-likelihood of the random effects |
| fexp | Exponential covariance function |
| f_lik_grad | Calculates the gradient of the full log-likelihood |
| f_lik_hess | Calculates the Hessian of the full log-likelihood |
| f_lik_optim | Simulated likelihood maximisation for the GLMM |
| genBlockD | Generates a block of the random effects covariance matrix |
| genD | Generates the covariance matrix of the random effects |
| glmmr-package | Design and analysis for generalised linear mixed models in R |
| gr | Group indicator covariance function |
| GradRobustStep | Hill-Climbing algorithm to identify optimal GLMM design |
| l_lik_hess | Optimises the log-likelihood of the observations conditional... |
| l_lik_optim | Optimises the log-likelihood of the observations conditional... |
| log_factorial_approx | Approximation to the log factorial |
| log_mv_gaussian_pdf | Log multivariate Gaussian probability density funciton |
| log_mvnd | Log density of multivariate normal distribution |
| match_rows | Generate matrix mapping between data frames |
| matern | Matern covariance function |
| mcnr_family | Returns the file name and type for MCNR function |
| mcnr_step | Newton-Raphson step for the MCMCML algorithm |
| MeanFunction | R6 Class representing a mean function function and data |
| myglm | Simplified version of fastglm's 'fastglm' function |
| nelder | Generates a block experimental structure using Nelder's... |
| nest_df | Generate nested block structure |
| parallel_crt | Generate a parallel cluster design |
| permutation_test_impl | Generates realisations of the permutational test statistic... |
| pexp | Power exponential covariance function |
| plot.glmmr.sim | Plotting method for glmmr.sim |
| print.glmmr.sim | Prints a glmmr simuation output |
| print.mcml | Prints an mcml fit output |
| progress_bar | Generates a progress bar |
| qscore_impl | The quasi-score statistic for a generalised linear mixed... |
| rcpparma_hello_world | Set of functions in example RcppArmadillo package |
| relist | Generate a list of a given structure with new values |
| remove_one_many_mat | Efficiently calculate the inverse of a sub-matrix |
| sqexp | Squared exponential covariance function |
| staircase_crt | Generate a staircase/diagonal trial design |
| stepped_wedge | Generate a stepped-wedge design |
| summarize.dfbeta | Method to summarise DFBETA output |
| summarize.errors | Method to summarise errors |
| summarize.stats | Method to summarise statistics |
| summary.mcml | Summarises an mcml fit output |
