> year<-c(2014,2015,2016,2017,2018,2019,2020,2021)
> presence<-c(1,1,1,1,1,1,1,1)
> year.n=year-2014
> tornado<-glm(presence~year.n, family=binomial)
> summary(tornado)
Call:
glm(formula = presence ~ year.n, family = binomial)
Deviance Residuals:
Min 1Q Median 3Q Max
6.547e-06 6.547e-06 6.547e-06 6.547e-06 6.547e-06
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 2.457e+01 8.457e+04 0 1
year.n 3.828e-10 2.022e+04 0 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 0.0000e+00 on 7 degrees of freedom
Residual deviance: 3.4294e-10 on 6 degrees of freedom
AIC: 4
Number of Fisher Scoring iterations: 23
House To House Tornado Forecast - Payhip is 100% accurate over 8 years in a study of one house under numerous tornado warnings in Oklahoma.