######################################################## # PATENT CITATION ANALYSIS library(mgcv) library(mgcViz) df <- read.csv("patent_sample_50k.csv") events <- df[,c('rec_pub_year','lag','rec_outd','jac_sim','cumu_cit_rec','tfe','sim')] non_events <- df[,c('rec_pub_year_2','lag_2','rec_outd_2','jac_sim_2','cumu_cit_rec_2','tfe_2','sim_2')] rec_pub_year <- cbind(events[,1],non_events[,1]) lag <- cbind(events[,2],non_events[,2]) rec_outd <- cbind(log(events[,3]),log(non_events[,3]))#log transform jac_sim <- cbind(events[,4],non_events[,4]) cumu_cit_rec <- cbind(log(events[,5]),log(non_events[,5]))#log transform tfe <- cbind(log(events[,6]+1),log(non_events[,6]+1))#log(x+1) transform sim <- cbind(events[,7],non_events[,7]) y <- rep(1,nrow(events)) W <- matrix(NA,nrow = nrow(events),ncol=2) W[,1] <- 1; W[,2] <- -1 model <- gam(formula = y ~ -1 + s(rec_pub_year, by=W)+ s(lag,by=W)+ #s(rec_outd,by=W)+ #s(jac_sim,by=W)+ #s(cumu_cit_rec,by=W)+ #s(tfe,by=W)+ s(sim,by=W), family="binomial"(link = 'logit'), method="REML") plot(model) model_viz <- getViz(model) plot(model_viz,selec=1)+theme_get() remdat<-read.csv2("manufacturing.csv") dim(remdat) head(remdat) attach(remdat) n<-nrow(remdat) ones<-rep(1,n) #set up data structure # reciprocity T<-cbind(r4a,non.r4a) I<-cbind(ones,-ones) # sender and receiver effects S<-cbind(as.factor(s),as.factor(non.s)) R<-cbind(as.factor(r),as.factor(non.r)) manu.rem<-gam(ones~ -1 + s(T,by=I) + s(S,by=I,bs="re")+ s(R,by=I,bs="re"), family=binomial) summary(manu.rem)