Description Usage Arguments Details Value See Also Examples
This function calculates, for each covariate in the model (except the intercept), the p-value of a likelihood ratio test comparing the original fitted NHPP with the model excluding that covariate from the linear predictor.
1 | LRTpv.fun(mlePP)
|
mlePP |
An object of class |
A LRT is carried for all the covariates in the linear predictor except the intercept. If the model has not an intercept and there is only one covariate, no test can be carried out.
A matrix with one column, which contains the LRT p-values for all the covariates in the model (except the intercept)
fitPP.fun
, testlik.fun
, dropAIC.fun
, addAIC.fun
1 2 3 4 5 6 7 8 9 10 11 12 | data(BarTxTn)
covB<-cbind(cos(2*pi*BarTxTn$dia/365), sin(2*pi*BarTxTn$dia/365),
BarTxTn$TTx,BarTxTn$Txm31,BarTxTn$Txm31**2)
BarEv<-POTevents.fun(T=BarTxTn$Tx,thres=318,
date=cbind(BarTxTn$ano,BarTxTn$mes,BarTxTn$dia))
mod1B<-fitPP.fun(tind=TRUE,covariates=covB,
posE=BarEv$Px, inddat=BarEv$inddat,
tit="BAR Tx; cos, sin, TTx, Txm31, Txm31**2",
start=list(b0=-100,b1=1,b2=10,b3=0,b4=0,b5=0),dplot=FALSE, modCI=FALSE)
LRTpv.fun(mod1B)
|
Loading required package: stats4
Number of events: 137
Number of excesses over threshold 318 : 253
Number of observations not used in the estimation process: 116
Total number of time observations: 8415
Number of events: 137
Convergence code: 0
Convergence attained
Loglikelihood: -522.727
Estimated coefficients:
b0 b1 b2 b3 b4 b5
-89.289 2.534 1.425 -0.006 0.557 -0.001
Full coefficients:
b0 b1 b2 b3 b4 b5
-89.289 2.534 1.425 -0.006 0.557 -0.001
attr(,"TypeCoeff")
[1] "Fixed: No fixed parameters"
The p-values of the LRT comparing the initial model and the model without the covariate
p-values
Covariate1 0.034
Covariate2 0.000
Covariate3 0.634
Covariate4 0.000
Covariate5 0.000
p-values
Covariate1 3.423331e-02
Covariate2 7.105427e-14
Covariate3 6.338780e-01
Covariate4 6.936213e-08
Covariate5 0.000000e+00
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.