bombay | Bombay data set |
coef-fitsir-method | Extract parameter of a fit |
dispersion | S4 method for finding a dispersion parameter |
dispersion-fitsir-method | Find dispersion parameter |
Eval | S4 generic for evaluate an object |
Eval-loglik.fitsir-method | Evaluate log likelihood model |
fitsir | fitting function |
fitsir-class | Class "fitsir". Result of SIR model fitting based on Maximum... |
grad | S4 generic for computing a gradient |
grad-loglik.fitsir-method | Evaluate the gradient of a model |
harbin | 1912 Harbin plague data set |
hessian | S4 generic for computing a hessian |
hessian-loglik.fitsir-method | Evaluate the hessian of a model |
initialize_hessian | initialize the hessian model |
initialize-loglik.fitsir-method | the initializer for loglik.fitsir |
loglik.fitsir-class | Class representing log-likelihood models used to fit the SIR... |
mledsp | Maximum likelihood estimate of negative binomial dispersion... |
phila1918 | 1918 Philadelphia flu data set |
plot-fitsir-missing-method | Plot a fitsir object |
predict-fitsir-method | Forecast from an SIR fit and find confidence interval |
residuals-fitsir-method | Find residuals between the fit and the data |
select_model | Select likelihood model |
show-summary.fitsir-method | Show summary of a fit |
SIR.detsim | deterministic trajectory of SIR |
SIR.detsim.hessian | integrate second order sensitivities |
SIR.grad | gradient function (solves with S,log(I) for stability) |
SIR.hessian | find Hessian |
SIR.logLik | Log-likelihood for SIR trajectory |
SIR.sensitivity | Gradient of negative log likelihood with respect to each... |
smooth.spline2 | Fit a spline to an epidemic data |
startfun | Starting function |
summarize.pars | Summarize parameters |
summary.fitsir-class | Class "summary.fitsir". Summary of SIR model fit |
summary-fitsir-method | Summarize the fit |
Transform | S4 generic for transforming an object |
Transform-loglik.fitsir-method | Transform the model |
trans.pars | transform parameters |
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