README for CompoundEvents

CompoundEvents

Tools for extracting occurrences, assessing potential driving factors, predicting occurrences, and quantifying impacts of compound events in hydrology and climatology.

Installation

You can install the development version of CompoundEvents like so:

install.packages("CompoundEvents")

Features / Functionality

• Extract occurrences of compound events (e.g., dry-hot, wet-hot, dry-cold).
• Assess potential driving factors using logistic regression.
• Predict occurrences of compound events.
• Quantify impacts (e.g., likelihood multiplication factor).
• Compute standardized compound event indicators.

Dependencies

• R (≥ 4.0.0)
• Imports: stats, pROC, mvtnorm
• Suggests: testthat (≥ 3.0.0)

License

This package is licensed under the GPL-3 license.

Author Information

• Author and Maintainer: Zengchao Hao
• Contact: z.hao4univ@gmail.com

Example

This is a basic example which shows you how to solve a common problem:

library(CompoundEvents)
## basic example code

data<-dfptng
summary(dfptng)
#>       pre               tem              nino               gpp        
#>  Min.   :  0.000   Min.   : 6.973   Min.   :-2.18000   Min.   :0.2372  
#>  1st Qu.:  8.028   1st Qu.:13.392   1st Qu.:-0.59000   1st Qu.:0.4407  
#>  Median : 47.063   Median :17.990   Median :-0.09000   Median :1.2563  
#>  Mean   : 62.401   Mean   :16.748   Mean   :-0.04332   Mean   :1.9255  
#>  3rd Qu.:103.535   3rd Qu.:19.994   3rd Qu.: 0.44250   3rd Qu.:3.2315  
#>  Max.   :299.510   Max.   :23.718   Max.   : 2.57000   Max.   :5.2647  
#>                                                        NA's   :348

## Compute the event occurrence for a month

mp<-data$pre[seq(2, length(data$pre), by = 12)]
mt<-data$tem[seq(2, length(data$tem), by = 12)]
p0=50
t0=50
Y<-GetDH(mp,mt, p0, t0)

You’ll still need to render README.Rmd regularly, to keep README.md up-to-date. devtools::build_readme() is handy for this