library(openxlsx)
b<-read.xlsx("data18-22IQR.xlsx")
b$date<-as.Date(b$date,origin="1899-12-30")
b$dow<-ifelse(b$dow=="Saturday"|b$dow=="Sunday",0,1)
b$dow<-factor(b$dow,levels = c(0,1),labels = c("weekend","weekday"))
b$holiday<-factor(b$holiday,levels = c(0,1),labels = c("nonholiday","holiday"))
library(mgcv)
library(splines)
library(ggplot2)
library(dlnm)
library(reshape2)


####
cb.TM<-crossbasis(b$temp,lag = 7,argvar = list(fun="ns",df=3),arglag = list(fun="ns",df=3))
cb.pm2.5<-crossbasis(b$PM25,lag=7,argvar = list(fun="lin"),arglag = list(fun="ns",df=3))
cb.pm10<-crossbasis(b$PM10,lag=7,argvar = list(fun="lin"),arglag = list(fun="ns",df=3))
cb.SO2<-crossbasis(b$SO2,lag=7,argvar = list(fun="lin"),arglag = list(fun="ns",df=3))
cb.CO<-crossbasis(b$CO,lag=7,argvar = list(fun="lin"),arglag = list(fun="ns",df=3))
cb.NO2<-crossbasis(b$NO2,lag=7,argvar = list(fun="lin"),arglag = list(fun="ns",df=3))

model1<-glm(b$morb~ cb.SO2+cb.TM+ns(b$time,df=9*5)+b$holiday+b$dow,family=quasipoisson,data=b)
pred.SO2<-crosspred(cb.SO2,model1,cen=0.8379333,at=0.8379333:1.8379333,bylag =1,cumul = T)

E1<-pred.SO2$cumRRfit["1.8379333",]
E2<-pred.SO2$cumRRlow["1.8379333",]
E3<-pred.SO2$cumRRhigh["1.8379333",]
E<-rbind(E1,E2,E3)
library(tidyr)
E4<-t(E)
E4<-as.data.frame(E4)
E4$E1<-round(E4$E1,3)
E4$E2<-round(E4$E2,3)
E4$E3<-round(E4$E3,3)
E4$a<-paste(E4$E1,E4$E2,sep = "(")
E4$b<-paste(E4$a,E4$E3,sep = "-")
E4$C<-paste(E4$b,"",")")
write.csv(E4,file = "E4.CSV")