drop1_p: Drop one possible covariate on GEV parameter based on...

In pengyuwei94/evreg: Extreme value regression modelling

Description

Drop a single term to either mu, sigma, and xi based on individual p value from Wald test.

Usage

drop1_p_mu(fit, alpha = 0.05)

drop1_p_sigma(fit, alpha = 0.05)

drop1_p_xi(fit, alpha = 0.05)

Arguments

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

Value

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 dropped 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 added covariate
pvalue	A data frame that contains p value with five decimal places of the dropped covariate if there is one.

Examples

### Fremantle sea levels

f3 <- gevreg(y = SeaLevel, data = evreg::fremantle[-1], mu = ~Year01 + SOI)
drop1_p_mu(f3)


### Annual Maximum and Minimum Temperature

P3 <- gevreg(y = TMX1, data = PORTw[, -1], mu = ~MTMAX + STDTMAX + STDMIN)
P  <- gevreg(y = TMX1, data = PORTw[, -1], sigma = ~MTMAX + MTMIN + STDTMAX)
P5 <- gevreg(y = TMX1, data = PORTw[, -1], xi = ~MTMAX + AOindex)
drop1_p_mu(P3)
drop1_p_sigma(P)
drop1_p_xi(P5)

pengyuwei94/evreg documentation built on Aug. 29, 2019, 1:06 p.m.