Survival Modeling with a Periodic Hazard Function
Censor and Trim
Create a cycloSurv object
Cyclomort: periodic survival modeling
Factorial analysis of seasonal survival models
Converting between Rho to Delta
Estimate periodic hazard function.
Produce initial parameter estimates based on mortality data
Log-likelihood function
Obtain log-likelihood value from a data set given a set of parameter v...
Plot cmfactorfit objects
Plot cmfit objects
Prediction method for cyclomort fits
Select the number of mortality seasons
Simulate periodic mortality process
Summary method for cyclomort factorial fit
Provide a short summary of cmfit (parameter estimates for periodic mor...
Summary method for cmfitlist objects
Wrapped Cauchy and Integrated Wrapped Cauchy functions
Modeling periodic mortality (or other time-to event) processes from right-censored data. Given observations of a process with a known period (e.g. 365 days, 24 hours), functions determine the number, intensity, timing, and duration of peaks of periods of elevated hazard within a period. The underlying model is a mixed wrapped Cauchy function fitted using maximum likelihoods (details in Gurarie et al. (2020) <doi:10.1111/2041-210X.13305>). The development of these tools was motivated by the strongly seasonal mortality patterns observed in many wild animal populations. Thus, the respective periods of higher mortality can be identified as "mortality seasons".