Man pages for akeyel/dfmip
Disease Forecast Model Intercomparison Project
| apply.always.absent.null | Always Absent Null |
| apply.ar1 | Apply Autoregressive 1 model |
| apply.historical.null | Apply Historical Null |
| apply.mean.value.null | Mean Value Null |
| apply.negative.binomial | Apply a negative binomial model |
| apply.null.models | Apply Null Models |
| apply.prior.year.null | Apply Prior Year Null |
| apply.random.incidence | Uniform Random Incidence |
| apply.stratified.incidence | Apply Stratified Incidence |
| apply.stratified.mean.null | Stratified Mean Null Model |
| apply.uniform | Uniform Null Model |
| assess.accuracy | Assess Accuracy |
| check.fields | Check Fields |
| create.month.day.vecs | Create a vector of days and months, starting with the first... |
| date.subset | Restrict data to a single date |
| dfmip | dfmip: Disease Forecast Model Inter-comparison Project... |
| dfmip.forecast | Disease Forecast Model Intercomparison Project (dfmip)... |
| dfmip.hindcasts | DFMIP Hindcasts |
| dfmip.to.cdc.challenge.format | Convert to CDC Forecast Challenge |
| evaluate.accuracy | Evaluate accuracy |
| expand.human.data | Expand human data |
| get.days | Function to get number of days in a year (copied from... |
| get.DOY | Get Day of Year, given year, month, and day |
| get_sampling_weeks | Get Weeks to sample |
| get.start.week | Goal is to be able to have predictions comparable to ArboMAP |
| human.data | Human Data |
| mean_min_max_table | Make a table with min, max, and mean values by location |
| mosq.data | Mosquito Data |
| Output_accuracy_assessment | Output accuracy assessment |
| plotbins | Bin plotting function for the cdc forecast bins |
| rf1.inputs | Random Forest Inputs |
| rf1.outputs | Random Forest 1 Model Outputs |
| run.null.models | Generate null models based on mean values |
| splitter | Split strings using strsplit in a way that can easily be used... |
| try.again | Try to fit a negative binomial, progressively modifying the... |
| weather.data | Weather Data |
