AIC.em.glm | Calculate the AIC of the em.glm model |
BIC.em.glm | Calculate the BIC of the em.glm model |
data.1 | Simulated data set |
deviance.em.glm | Model deviance (calculated from deviance residuals) |
dispersion | Pearson-based dispersion measurements of an 'em.glm' model. |
dprob.list | List of distribution functions accessed by family name... |
emax.glm | General linear regression via Expectation-Maximization. |
em.fit_numeric | Carry our the Newton-Raphson optimization of the parameters... |
em.fit_pracma | Carry our the Newton-Raphson optimization of the parameters... |
em.glm | Expectation Maximization glm. |
em.glm_numeric_fit | Numeric approximation routine |
em.glm_pracma_fit | Hessian routine |
IC.em.glm | General Information Criteria function |
init.fit | Method to initialize EM parameters. Carries out a single GLM... |
init.random | Method to initialize EM parameters. Purely standard normal... |
logLik.em.glm | Calculate log-likelihood of the EM model. |
make.dbinom | Build a Binomial log likelihood |
make.dpois | Build a Poisson log likelihood |
make.logLike | Construct a log-likelihood function in the parameters b, for... |
make_param_errors | Calculate parameter errors via inversion of the Hessian... |
plot.em.glm | Plot fit-parameters and errors |
plot.em.glm.summary | Error bar plot of coefficients and errors to inspect class... |
plot_probabilities | Probability plots for the K classes fit |
plot_probabilities.em.glm | Test Plot em.glm |
plot_probabilities.matrix | Plot the class probabilities, both compared to data set index... |
predict.em.glm | Predict values from an 'em.glm' model. |
residuals.em.glm | Deviance residuals for an 'em.glm' object. |
results_k25_n1000 | Simulated data set |
results_k25_n1000_e05 | Simulated data set |
results_simple | Simulated data set |
select_best | Select the best parameters from a set of results |
sim.1 | Simulated data set |
sim.2 | Simulated data set |
sim.3 | Simulated data set |
small.em | Carry out several short EM fits to test for optimal starting... |
summary.em.glm | Summarize EM glm coefficients. |
summary.small.em | Summarize a small.em class |
update_probabilities | Construct normalized class properties for a given set of... |
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