drop1_LRT: Drop one possible covariate on GEV parameter based on...
In pengyuwei94/evreg: Extreme value regression modelling

Description Usage Arguments Value Examples

Drop a single term to either mu, sigma, and xi based on likelihood-ratio-test.

drop1_LRT_mu(fit, alpha = 0.05)

drop1_LRT_sigma(fit, alpha = 0.05)

drop1_LRT_xi(fit, alpha = 0.05)

`fit`	An object of class `c("gev", "evreg")` returned from `gevreg` summarising the current model fit.
`alpha`	Significance level. Default value is 0.05..

An object (a list) of class c("gev", "evreg") summarising the new model fit (which may be the same as fit) and containing the following additional components

`Input_fit`	The input object of the class `c("gev", "evreg")`.
`Note`	A message that tells if a covariate has been added or not.
`Output_fit`	A list that contains formulae for the parameter, and the output object of the class `c("gev", "evreg")` if the output fit is different from the input fit.
`dropped_covariate`	A character vector shows dropped covariate
`pvalue`	A data frame that contains p value with five decimal places of the Likelihood-ratio-test.

### Annual Maximum and Minimum Temperature

P3 <- gevreg(y = TMX1, data = PORTw[, -1], mu = ~MTMAX + STDTMAX + STDMIN)
P4 <- gevreg(y = TMX1, data = PORTw[, -1], sigma = ~MTMAX + STDTMAX + STDMIN)
P5 <- gevreg(y = TMX1, data = PORTw[, -1], xi = ~MTMAX + AOindex)
drop1_LRT_mu(P3)
drop1_LRT_sigma(P4)
drop1_LRT_xi(P5)