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.Rhistory
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result<-tso(tsm)
result$outliers
?tso
tso(tsm,maxit.iloop = 1)
library(tsoutlier)
algorithm(dat)
library(forecast)
library(tsoutliers)
library(timeSeries)
algorithm(dat)
library(tsoutlier)
library("tsoutliers", lib.loc="~/R/win-library/3.3")
library("forecast", lib.loc="~/R/win-library/3.3")
library("timeSeries", lib.loc="~/R/win-library/3.3")
library("zoo", lib.loc="~/R/win-library/3.3")
ac<-algorithm(dat)
View(ac)
library(ggplot2)
tmp<-ac
plot_dia<-ggplot(tmp,aes(Date))+
geom_line(data = tmp,aes(Date,Predicted),size=2,col="steelblue")+
geom_point(data = tmp,aes(Date,Actual,col=Sensitivity))+
geom_ribbon(aes(ymin=lowerOffOutlierLimit,ymax=upperOffOutlierLimit),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')+
theme(axis.text= element_text(face = "bold",size = 7.5) ,
axis.title.y =element_blank() ,
axis.title.x =element_blank() ,
plot.title = element_text(size =11, face = "bold") ,
plot.subtitle = element_text(size = 12),legend.position = "None"
)+
scale_color_manual(values=c("0" = "#333BFF", "outlier" = "#CC6600"))
plot_dia
ggplot(tmp,aes(Date))+
geom_line(data = tmp,aes(Date,Predicted),size=2,col="steelblue")+
geom_point(data = tmp,aes(Date,Actual,col=Sensitivity))+
geom_ribbon(aes(ymin=lowerOffOutlierLimit,ymax=upperOffOutlierLimit),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
View(ac)
2751*.25
2751+
2751*.25
View(dat)
tmp<-ac
class(ac)
View(ac)
input<-dat
input[,2]<-as.numeric(input[,2])
dat<-input
if(nchar(dat[,1][1])>10){
seq_len<-nrow(dat)
input[,1]<-seq(as.Date("2000/1/1"), by = "day", length.out = seq_len)
input[,1]<-as.Date(as.character(input[,1]), format='%Y-%m-%d')
dat[,1]<-as.POSIXct(dat[,1])
}else {
dat[,1]<-as.Date(as.character(dat[,1]), format='%Y-%m-%d')
dat<-dat[order(dat[,1]),]
}
t_c<- timeseries_conversion(input[,2], order.by=input[,1])
tsm<-timeseries(t_c)
tsm
indx <- 1:length(dat[,1])
var.use <- dat[,2]
lo <- loess(var.use~indx)
predicted<-predict(lo)
temp<-var.use
temp
result<-tso(tsm,maxit.iloop = 1)
analysis<-result$outliers
analysis
nrow(analysis)!=0
result$yadj[result$times]
dat[,2][result$times]
class(dat[,2][result$times])
class(result$yadj[result$times])
dat[,2][result$times]<-result$yadj[result$times]
outlier<-list()
outlier[1:length(dat[,1])]<-0
outlier[analysis$ind]<-1
outlier
raw_limit<-sum(abs(var.use-dat[,2])/var.use)/length(result$times)
limit<-raw_limit*0.5
raw_limit
limit
chk<-unique((var.use-dat[,2])/var.use)[-1]
chk
if(sum(chk<limit)==0){
limit_s<-limit*0.5
} else{
limit<-limit*0.75
limit_s<-limit*0.5
}
if(sum(chk<limit)!=0){
limit<-limit*0.75
limit_s<-limit*0.75
}
limit
limit_s
temp<-dat[,2]
temp
temp +(temp*limit)/100
temp +(temp*limit)
View(temp +(temp*limit)/100,temp +(temp*limit))
View(cbind(temp +(temp*limit)/100,temp +(temp*limit)))
View(cbind(temp +(temp*limit)/100,input[,2],dat[,2],temp +(temp*limit),unlist(oulier)))
View(cbind(temp +(temp*limit)/100,input[,2],dat[,2],temp +(temp*limit),unlist(outlier)))
if(nrow(analysis)!=0){
dat[,2][result$times]<-result$yadj[result$times]
outlier<-list()
outlier[1:length(dat[,1])]<-0
outlier[analysis$ind]<-1
raw_limit<-sum(abs(var.use-dat[,2])/var.use)/length(result$times)
limit<-raw_limit*0.5
chk<-unique((var.use-dat[,2])/var.use)[-1]
if(sum(chk<limit)==0){
limit_s<-limit*0.5
} else{
limit<-limit*0.75
limit_s<-limit*0.5
}
if(sum(chk<limit)!=0){
limit<-limit*0.75
limit_s<-limit*0.75
}
temp<-dat[,2]
tmp<-data.frame(dat[,1],predicted,var.use,dat[,2],temp +(temp*limit)/100 ,temp -(temp*limit)/100,temp +(temp*limit_s[5]*2)/100 ,temp -(temp*limit_s[5]*2)/100,unlist(outlier))
} else{
temp<-dat[,2]
outlier<-list()
outlier[1:length(dat[,1])]<-0
limit<-0.5
limit_s<-limit*0.6
tmp<-data.frame(dat[,1],predicted,var.use,temp +(temp*limit)/100 ,temp -(temp*limit)/100,temp +(temp*limit_s[5]*2)/100 ,temp -(temp*limit_s[5]*2)/100,unlist(outlier))
}
if(nrow(analysis)!=0){
dat[,2][result$times]<-result$yadj[result$times]
outlier<-list()
outlier[1:length(dat[,1])]<-0
outlier[analysis$ind]<-1
raw_limit<-sum(abs(var.use-dat[,2])/var.use)/length(result$times)
limit<-raw_limit*0.5
chk<-unique((var.use-dat[,2])/var.use)[-1]
if(sum(chk<limit)==0){
limit_s<-limit*0.5
} else{
limit<-limit*0.75
limit_s<-limit*0.5
}
if(sum(chk<limit)!=0){
limit<-limit*0.75
limit_s<-limit*0.75
}
temp<-dat[,2]
tmp<-data.frame(dat[,1],predicted,var.use,dat[,2],temp +(temp*limit) ,temp -(temp*limit),temp +(temp*limit_s),temp -(temp*limit_s),unlist(outlier))
} else{
temp<-dat[,2]
outlier<-list()
outlier[1:length(dat[,1])]<-0
limit<-0.5
limit_s<-limit*0.6
tmp<-data.frame(dat[,1],predicted,var.use,temp +(temp*limit) ,temp -(temp*limit),temp +(temp*limit_s),temp -(temp*limit_s),unlist(outlier))
}
View(tmp)
colnames(tmp)<-c("Date","Predicted","Actual","upperOffOutlierLimit","lowerOffOutlierLimit","upperSafe3rdQuantLimit","lowerSafe3rdQuantLimit","Sensitivity")
library(tsoutlier)
dat
tmp<-tsoutlier::algorithm(dat)
algorithm(dat)
ac<-read.csv("/Users/kartikeya kirar/Downloads/jimmy/d2.csv",sep = "\t")
tmp<-tsoutlier::algorithm(ac)
tmp<-tsoutlier::algorithm(ac)
library(tsoutlier)
tmp<-tsoutlier::algorithm(ac)
View(tmp)
ac[,1]
tmp<-tsoutlier::algorithm(ac)
library(tsoutlier)
tmp<-tsoutlier::algorithm(ac)
.libPaths()
with_libpaths(new = "/usr/lib/R/library", install_github('tsoutlier', 'kartikeyakirar'))
library(devtools)
with_libpaths(new = "/usr/lib/R/library", install_github('tsoutlier', 'kartikeyakirar'))
library(tsoutlier)
tmp<-tsoutlier::algorithm(ac)
ggplot(tmp,aes(Date))+
geom_line(data = tmp,aes(Date,Predicted),size=2,col="steelblue")+
geom_point(data = tmp,aes(Date,Actual,col=Sensitivity))+
geom_ribbon(aes(ymin=lowerOffOutlierLimit,ymax=upperOffOutlierLimit),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
dat[,1]<-as.Date(as.character(dat[,1]), format='%Y-%m-%d')
tmp[,1]<-as.Date(as.character(tmp[,1]), format='%Y%m%d')
ggplot(tmp,aes(Date))+
geom_line(data = tmp,aes(Date,Predicted),size=2,col="steelblue")+
geom_point(data = tmp,aes(Date,Actual,col=Sensitivity))+
geom_ribbon(aes(ymin=lowerOffOutlierLimit,ymax=upperOffOutlierLimit),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
library(tsoutlier)
tmp[,1]<-as.Date(as.character(tmp[,1]), format='%Y%m%d')
tmp<-tsoutlier::algorithm(ac)
tmp[,1]<-as.Date(as.character(tmp[,1]), format='%Y%m%d')
ggplot(tmp,aes(Date))+
geom_line(data = tmp,aes(Date,Predicted),size=2,col="steelblue")+
geom_point(data = tmp,aes(Date,Actual,col=Sensitivity))+
geom_ribbon(aes(ymin=lowerOffOutlierLimit,ymax=upperOffOutlierLimit),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
ggplot(tmp,aes(Date))+
geom_line(data = tmp,aes(Date,Predicted),size=2,col="steelblue")+
geom_point(data = tmp,aes(Date,Actual,col=Sensitivity))+
geom_ribbon(aes(ymin=lowerOffOutlierLimit,ymax=upperOffOutlierLimit),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
y<-tmp
y<-tmp[,1:5]
y$ck<-(y$Predicted+y$Predicted*0.3)
View(y)
tmp[tmp$Sensitivity!=1,]
y<-tmp[tmp$Sensitivity!=1,]
y$Predicted-y$Actual
abs(y$Predicted-y$Actual)/y$Predicted
max(abs(y$Predicted-y$Actual)/y$Predicted)
w<-max(abs(y$Predicted-y$Actual)/y$Predicted)
y<-tmp[,1:5]
y$ck<-(y$Predicted+y$Predicted*w)
y$ck1<-(y$Predicted-y$Predicted*w)
tmp<-tsoutlier::algorithm(ac[300:350,])
tmp<-tsoutlier::algorithm(ac[300:350,])
tmp[,1]<-as.Date(as.character(tmp[,1]), format='%Y%m%d')
q<-tmp[tmp$Sensitivity!=1,]
w<-max(abs(q$Predicted-q$Actual)/q$Predicted)
w
y<-tmp[,1:5]
y$ck<-(y$Predicted+y$Predicted*w)
y$ck1<-(y$Predicted-y$Predicted*w)
ggplot(tmp,aes(Date))+
geom_line(data = tmp,aes(Date,Predicted),size=2,col="steelblue")+
geom_point(data = tmp,aes(Date,Actual,col=Sensitivity))+
geom_ribbon(aes(ymin=lowerOffOutlierLimit,ymax=upperOffOutlierLimit),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
library(tsoutlier)
tmp<-tsoutlier::algorithm(ac)
tmp[,1]<-as.Date(as.character(tmp[,1]), format='%Y%m%d')
q<-tmp[tmp$Sensitivity!=1,]
w<-max(abs(q$Predicted-q$Actual)/q$Predicted)
y<-tmp[,1:5]
y$ck<-(y$Predicted+y$Predicted*w)
y$ck1<-(y$Predicted-y$Predicted*w)
ggplot(tmp,aes(Date))+
geom_line(data = tmp,aes(Date,Predicted),size=2,col="steelblue")+
geom_point(data = tmp,aes(Date,Actual,col=Sensitivity))+
geom_ribbon(aes(ymin=lowerOffOutlierLimit,ymax=upperOffOutlierLimit),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
ggplot(y,aes(Date))+
geom_line(data = y,aes(Date,Predicted),size=2,col="steelblue")+
geom_point(data = y,aes(Date,Actual,col=Sensitivity))+
geom_ribbon(aes(ymin=ck,ymax=ck),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
y$sen<-tmp$Sensitivity
ggplot(y,aes(Date))+
geom_line(data = y,aes(Date,Predicted),size=2,col="steelblue")+
geom_point(data = y,aes(Date,Actual,col=sen))+
geom_ribbon(aes(ymin=ck,ymax=ck),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
ggplot(y,aes(Date))+
geom_line(data = y,aes(Date,Predicted),size=2,col="steelblue")+
geom_point(data = y,aes(Date,Actual,col=sen))+
geom_ribbon(aes(ymin=ck,ymax=ck1),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
tmp<-tsoutlier::algorithm(ac[300:350,])
tmp[,1]<-as.Date(as.character(tmp[,1]), format='%Y%m%d')
q<-tmp[tmp$Sensitivity!=1,]
w<-max(abs(q$Predicted-q$Actual)/q$Predicted)
y<-tmp[,1:5]
y$ck<-(y$Predicted+y$Predicted*w)
y$ck1<-(y$Predicted-y$Predicted*w)
y$sen<-tmp$Sensitivity
ggplot(tmp,aes(Date))+
geom_line(data = tmp,aes(Date,Predicted),size=2,col="steelblue")+
geom_point(data = tmp,aes(Date,Actual,col=Sensitivity))+
geom_ribbon(aes(ymin=lowerOffOutlierLimit,ymax=upperOffOutlierLimit),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
ggplot(y,aes(Date))+
geom_line(data = y,aes(Date,Predicted),size=2,col="steelblue")+
geom_point(data = y,aes(Date,Actual,col=sen))+
geom_ribbon(aes(ymin=ck,ymax=ck1),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
ggplot(tmp,aes(Date))+
geom_line(data = tmp,aes(Date,Predicted),size=2,col="steelblue")+
geom_point(data = tmp,aes(Date,Actual,col=Sensitivity))+
geom_ribbon(aes(ymin=lowerOffOutlierLimit,ymax=upperOffOutlierLimit),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
ggplot(tmp,aes(Date))+
#geom_line(data = tmp,aes(Date,Predicted),size=2,col="steelblue")+
geom_line(data = tmp,aes(Date,Actual,col=Sensitivity))+
geom_ribbon(aes(ymin=lowerOffOutlierLimit,ymax=upperOffOutlierLimit),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
ggplot(tmp,aes(Date))+
geom_point(data = tmp,aes(Date,Actual),size=2,col="steelblue")+
geom_line(data = tmp,aes(Date,Actual,col=Sensitivity))+
geom_ribbon(aes(ymin=lowerOffOutlierLimit,ymax=upperOffOutlierLimit),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
ggplot(tmp,aes(Date))+
geom_point(data = tmp,aes(Date,Actual),size=2,col=Sensitivity)+
geom_line(data = tmp,aes(Date,Actual,col=Sensitivity))+
geom_ribbon(aes(ymin=lowerOffOutlierLimit,ymax=upperOffOutlierLimit),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
ggplot(tmp,aes(Date))+
geom_point(data = tmp,aes(Date,Actual,size=2,col=Sensitivity))+
geom_line(data = tmp,aes(Date,Actual,col=Sensitivity))+
geom_ribbon(aes(ymin=lowerOffOutlierLimit,ymax=upperOffOutlierLimit),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
ggplot(tmp,aes(Date))+
geom_point(data = tmp,aes(Date,Actual,size=1,col=Sensitivity))+
geom_line(data = tmp,aes(Date,Actual,col=Sensitivity))+
geom_ribbon(aes(ymin=lowerOffOutlierLimit,ymax=upperOffOutlierLimit),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
result<-tso(tsm,maxit.iloop = 1,maxit.oloop=1)
?tso
tmp<-tsoutlier::algorithm(ac[300:350,])
tmp[,1]<-as.Date(as.character(tmp[,1]), format='%Y%m%d')
q<-tmp[tmp$Sensitivity!=1,]
w<-max(abs(q$Predicted-q$Actual)/q$Predicted)
y<-tmp[,1:5]
y$ck<-(y$Predicted+y$Predicted*w)
y$ck1<-(y$Predicted-y$Predicted*w)
y$sen<-tmp$Sensitivity
ggplot(tmp,aes(Date))+
geom_line(data = tmp,aes(Date,Predicted),size=2,col="steelblue")+
geom_point(data = tmp,aes(Date,Actual,col=Sensitivity))+
geom_ribbon(aes(ymin=lowerOffOutlierLimit,ymax=upperOffOutlierLimit),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
View(tmp)
ggplot(tmp,aes(Date))+
geom_line(data = tmp,aes(Date,Predicted),size=2,col="steelblue")+
geom_point(data = tmp,aes(Date,Actual,col=Sensitivity))+
geom_ribbon(aes(ymin=lowerOffOutlierLimit,ymax=upperOffOutlierLimit),alpha=.25,fill="steelblue")+geom_ribbon(aes(ymin=lowerSafe3rdQuantLimit,ymax=upperSafe3rdQuantLimit),alpha=.25,fill="steelblue")+
labs(title='Outlier Detection')
tmp<-data.frame(dat[,1],predicted,var.use,temp +(temp*limit) ,temp -(temp*limit),temp +(temp*limit_s),temp -(temp*limit_s),unlist(outlier))
library(tsoutlier)
jsonlite::fromJSON("[{"ga:date":"2017-05-22 13:00:00","ga:users":"28.00"},{"ga:date":"2017-05-22 14:00:00","ga:users":"5.00"},{"ga:date":"2017-05-22 22:00:00","ga:users":"37.00"},{"ga:date":"2017-05-23 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-23 10:00:00","ga:users":"130.00"},{"ga:date":"2017-05-23 16:00:00","ga:users":"6.00"},{"ga:date":"2017-05-24 16:00:00","ga:users":"32.00"},{"ga:date":"2017-05-25 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-25 10:00:00","ga:users":"8.00"},{"ga:date":"2017-05-29 10:00:00","ga:users":"4.00"},{"ga:date":"2017-05-29 15:00:00","ga:users":"2.00"},{"ga:date":"2017-05-30 10:00:00","ga:users":"16.00"},{"ga:date":"2017-05-31 09:00:00","ga:users":"6.00"},{"ga:date":"2017-05-31 10:00:00","ga:users":"4.00"},{"ga:date":"2017-06-01 09:00:00","ga:users":"27.00"},{"ga:date":"2017-06-13 20:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 07:00:00","ga:users":"4.00"},{"ga:date":"2017-06-15 17:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 21:00:00","ga:users":"1.00"},{"ga:date":"2017-06-16 10:00:00","ga:users":"2.00"},{"ga:date":"2017-06-16 14:00:00","ga:users":"4.00"},{"ga:date":"2017-06-16 15:00:00","ga:users":"1.00"},{"ga:date":"2017-05-22 13:00:00","ga:users":"28.00"},{"ga:date":"2017-05-22 14:00:00","ga:users":"5.00"},{"ga:date":"2017-05-22 22:00:00","ga:users":"37.00"},{"ga:date":"2017-05-23 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-23 10:00:00","ga:users":"130.00"},{"ga:date":"2017-05-23 16:00:00","ga:users":"6.00"},{"ga:date":"2017-05-24 16:00:00","ga:users":"32.00"},{"ga:date":"2017-05-25 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-25 10:00:00","ga:users":"8.00"},{"ga:date":"2017-05-29 10:00:00","ga:users":"4.00"},{"ga:date":"2017-05-29 15:00:00","ga:users":"2.00"},{"ga:date":"2017-05-30 10:00:00","ga:users":"16.00"},{"ga:date":"2017-05-31 09:00:00","ga:users":"6.00"},{"ga:date":"2017-05-31 10:00:00","ga:users":"4.00"},{"ga:date":"2017-06-01 09:00:00","ga:users":"27.00"},{"ga:date":"2017-06-13 20:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 07:00:00","ga:users":"4.00"},{"ga:date":"2017-06-15 17:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 21:00:00","ga:users":"1.00"},{"ga:date":"2017-06-16 10:00:00","ga:users":"2.00"},{"ga:date":"2017-06-16 14:00:00","ga:users":"4.00"},{"ga:date":"2017-06-16 15:00:00","ga:users":"1.00"},{"ga:date":"2017-05-22 13:00:00","ga:users":"28.00"},{"ga:date":"2017-05-22 14:00:00","ga:users":"5.00"},{"ga:date":"2017-05-22 22:00:00","ga:users":"37.00"},{"ga:date":"2017-05-23 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-23 10:00:00","ga:users":"130.00"},{"ga:date":"2017-05-23 16:00:00","ga:users":"6.00"},{"ga:date":"2017-05-24 16:00:00","ga:users":"32.00"},{"ga:date":"2017-05-25 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-25 10:00:00","ga:users":"8.00"},{"ga:date":"2017-05-29 10:00:00","ga:users":"4.00"},{"ga:date":"2017-05-29 15:00:00","ga:users":"2.00"},{"ga:date":"2017-05-30 10:00:00","ga:users":"16.00"},{"ga:date":"2017-05-31 09:00:00","ga:users":"6.00"},{"ga:date":"2017-05-31 10:00:00","ga:users":"4.00"},{"ga:date":"2017-06-01 09:00:00","ga:users":"27.00"},{"ga:date":"2017-06-13 20:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 07:00:00","ga:users":"4.00"},{"ga:date":"2017-06-15 17:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 21:00:00","ga:users":"1.00"},{"ga:date":"2017-06-16 10:00:00","ga:users":"2.00"},{"ga:date":"2017-06-16 14:00:00","ga:users":"4.00"},{"ga:date":"2017-06-16 15:00:00","ga:users":"1.00"},{"ga:date":"2017-05-22 13:00:00","ga:users":"28.00"},{"ga:date":"2017-05-22 14:00:00","ga:users":"5.00"},{"ga:date":"2017-05-22 22:00:00","ga:users":"37.00"},{"ga:date":"2017-05-23 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-23 10:00:00","ga:users":"130.00"},{"ga:date":"2017-05-23 16:00:00","ga:users":"6.00"},{"ga:date":"2017-05-24 16:00:00","ga:users":"32.00"},{"ga:date":"2017-05-25 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-25 10:00:00","ga:users":"8.00"},{"ga:date":"2017-05-29 10:00:00","ga:users":"4.00"},{"ga:date":"2017-05-29 15:00:00","ga:users":"2.00"},{"ga:date":"2017-05-30 10:00:00","ga:users":"16.00"},{"ga:date":"2017-05-31 09:00:00","ga:users":"6.00"},{"ga:date":"2017-05-31 10:00:00","ga:users":"4.00"},{"ga:date":"2017-06-01 09:00:00","ga:users":"27.00"},{"ga:date":"2017-06-13 20:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 07:00:00","ga:users":"4.00"},{"ga:date":"2017-06-15 17:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 21:00:00","ga:users":"1.00"},{"ga:date":"2017-06-16 10:00:00","ga:users":"2.00"}]")
jsonlite::fromJSON('[{"ga:date":"2017-05-22 13:00:00","ga:users":"28.00"},{"ga:date":"2017-05-22 14:00:00","ga:users":"5.00"},{"ga:date":"2017-05-22 22:00:00","ga:users":"37.00"},{"ga:date":"2017-05-23 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-23 10:00:00","ga:users":"130.00"},{"ga:date":"2017-05-23 16:00:00","ga:users":"6.00"},{"ga:date":"2017-05-24 16:00:00","ga:users":"32.00"},{"ga:date":"2017-05-25 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-25 10:00:00","ga:users":"8.00"},{"ga:date":"2017-05-29 10:00:00","ga:users":"4.00"},{"ga:date":"2017-05-29 15:00:00","ga:users":"2.00"},{"ga:date":"2017-05-30 10:00:00","ga:users":"16.00"},{"ga:date":"2017-05-31 09:00:00","ga:users":"6.00"},{"ga:date":"2017-05-31 10:00:00","ga:users":"4.00"},{"ga:date":"2017-06-01 09:00:00","ga:users":"27.00"},{"ga:date":"2017-06-13 20:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 07:00:00","ga:users":"4.00"},{"ga:date":"2017-06-15 17:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 21:00:00","ga:users":"1.00"},{"ga:date":"2017-06-16 10:00:00","ga:users":"2.00"},{"ga:date":"2017-06-16 14:00:00","ga:users":"4.00"},{"ga:date":"2017-06-16 15:00:00","ga:users":"1.00"},{"ga:date":"2017-05-22 13:00:00","ga:users":"28.00"},{"ga:date":"2017-05-22 14:00:00","ga:users":"5.00"},{"ga:date":"2017-05-22 22:00:00","ga:users":"37.00"},{"ga:date":"2017-05-23 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-23 10:00:00","ga:users":"130.00"},{"ga:date":"2017-05-23 16:00:00","ga:users":"6.00"},{"ga:date":"2017-05-24 16:00:00","ga:users":"32.00"},{"ga:date":"2017-05-25 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-25 10:00:00","ga:users":"8.00"},{"ga:date":"2017-05-29 10:00:00","ga:users":"4.00"},{"ga:date":"2017-05-29 15:00:00","ga:users":"2.00"},{"ga:date":"2017-05-30 10:00:00","ga:users":"16.00"},{"ga:date":"2017-05-31 09:00:00","ga:users":"6.00"},{"ga:date":"2017-05-31 10:00:00","ga:users":"4.00"},{"ga:date":"2017-06-01 09:00:00","ga:users":"27.00"},{"ga:date":"2017-06-13 20:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 07:00:00","ga:users":"4.00"},{"ga:date":"2017-06-15 17:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 21:00:00","ga:users":"1.00"},{"ga:date":"2017-06-16 10:00:00","ga:users":"2.00"},{"ga:date":"2017-06-16 14:00:00","ga:users":"4.00"},{"ga:date":"2017-06-16 15:00:00","ga:users":"1.00"},{"ga:date":"2017-05-22 13:00:00","ga:users":"28.00"},{"ga:date":"2017-05-22 14:00:00","ga:users":"5.00"},{"ga:date":"2017-05-22 22:00:00","ga:users":"37.00"},{"ga:date":"2017-05-23 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-23 10:00:00","ga:users":"130.00"},{"ga:date":"2017-05-23 16:00:00","ga:users":"6.00"},{"ga:date":"2017-05-24 16:00:00","ga:users":"32.00"},{"ga:date":"2017-05-25 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-25 10:00:00","ga:users":"8.00"},{"ga:date":"2017-05-29 10:00:00","ga:users":"4.00"},{"ga:date":"2017-05-29 15:00:00","ga:users":"2.00"},{"ga:date":"2017-05-30 10:00:00","ga:users":"16.00"},{"ga:date":"2017-05-31 09:00:00","ga:users":"6.00"},{"ga:date":"2017-05-31 10:00:00","ga:users":"4.00"},{"ga:date":"2017-06-01 09:00:00","ga:users":"27.00"},{"ga:date":"2017-06-13 20:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 07:00:00","ga:users":"4.00"},{"ga:date":"2017-06-15 17:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 21:00:00","ga:users":"1.00"},{"ga:date":"2017-06-16 10:00:00","ga:users":"2.00"},{"ga:date":"2017-06-16 14:00:00","ga:users":"4.00"},{"ga:date":"2017-06-16 15:00:00","ga:users":"1.00"},{"ga:date":"2017-05-22 13:00:00","ga:users":"28.00"},{"ga:date":"2017-05-22 14:00:00","ga:users":"5.00"},{"ga:date":"2017-05-22 22:00:00","ga:users":"37.00"},{"ga:date":"2017-05-23 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-23 10:00:00","ga:users":"130.00"},{"ga:date":"2017-05-23 16:00:00","ga:users":"6.00"},{"ga:date":"2017-05-24 16:00:00","ga:users":"32.00"},{"ga:date":"2017-05-25 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-25 10:00:00","ga:users":"8.00"},{"ga:date":"2017-05-29 10:00:00","ga:users":"4.00"},{"ga:date":"2017-05-29 15:00:00","ga:users":"2.00"},{"ga:date":"2017-05-30 10:00:00","ga:users":"16.00"},{"ga:date":"2017-05-31 09:00:00","ga:users":"6.00"},{"ga:date":"2017-05-31 10:00:00","ga:users":"4.00"},{"ga:date":"2017-06-01 09:00:00","ga:users":"27.00"},{"ga:date":"2017-06-13 20:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 07:00:00","ga:users":"4.00"},{"ga:date":"2017-06-15 17:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 21:00:00","ga:users":"1.00"},{"ga:date":"2017-06-16 10:00:00","ga:users":"2.00"}]')
'
qwe<-jsonlite::fromJSON('[{"ga:date":"2017-05-22 13:00:00","ga:users":"28.00"},{"ga:date":"2017-05-22 14:00:00","ga:users":"5.00"},{"ga:date":"2017-05-22 22:00:00","ga:users":"37.00"},{"ga:date":"2017-05-23 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-23 10:00:00","ga:users":"130.00"},{"ga:date":"2017-05-23 16:00:00","ga:users":"6.00"},{"ga:date":"2017-05-24 16:00:00","ga:users":"32.00"},{"ga:date":"2017-05-25 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-25 10:00:00","ga:users":"8.00"},{"ga:date":"2017-05-29 10:00:00","ga:users":"4.00"},{"ga:date":"2017-05-29 15:00:00","ga:users":"2.00"},{"ga:date":"2017-05-30 10:00:00","ga:users":"16.00"},{"ga:date":"2017-05-31 09:00:00","ga:users":"6.00"},{"ga:date":"2017-05-31 10:00:00","ga:users":"4.00"},{"ga:date":"2017-06-01 09:00:00","ga:users":"27.00"},{"ga:date":"2017-06-13 20:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 07:00:00","ga:users":"4.00"},{"ga:date":"2017-06-15 17:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 21:00:00","ga:users":"1.00"},{"ga:date":"2017-06-16 10:00:00","ga:users":"2.00"},{"ga:date":"2017-06-16 14:00:00","ga:users":"4.00"},{"ga:date":"2017-06-16 15:00:00","ga:users":"1.00"},{"ga:date":"2017-05-22 13:00:00","ga:users":"28.00"},{"ga:date":"2017-05-22 14:00:00","ga:users":"5.00"},{"ga:date":"2017-05-22 22:00:00","ga:users":"37.00"},{"ga:date":"2017-05-23 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-23 10:00:00","ga:users":"130.00"},{"ga:date":"2017-05-23 16:00:00","ga:users":"6.00"},{"ga:date":"2017-05-24 16:00:00","ga:users":"32.00"},{"ga:date":"2017-05-25 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-25 10:00:00","ga:users":"8.00"},{"ga:date":"2017-05-29 10:00:00","ga:users":"4.00"},{"ga:date":"2017-05-29 15:00:00","ga:users":"2.00"},{"ga:date":"2017-05-30 10:00:00","ga:users":"16.00"},{"ga:date":"2017-05-31 09:00:00","ga:users":"6.00"},{"ga:date":"2017-05-31 10:00:00","ga:users":"4.00"},{"ga:date":"2017-06-01 09:00:00","ga:users":"27.00"},{"ga:date":"2017-06-13 20:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 07:00:00","ga:users":"4.00"},{"ga:date":"2017-06-15 17:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 21:00:00","ga:users":"1.00"},{"ga:date":"2017-06-16 10:00:00","ga:users":"2.00"},{"ga:date":"2017-06-16 14:00:00","ga:users":"4.00"},{"ga:date":"2017-06-16 15:00:00","ga:users":"1.00"},{"ga:date":"2017-05-22 13:00:00","ga:users":"28.00"},{"ga:date":"2017-05-22 14:00:00","ga:users":"5.00"},{"ga:date":"2017-05-22 22:00:00","ga:users":"37.00"},{"ga:date":"2017-05-23 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-23 10:00:00","ga:users":"130.00"},{"ga:date":"2017-05-23 16:00:00","ga:users":"6.00"},{"ga:date":"2017-05-24 16:00:00","ga:users":"32.00"},{"ga:date":"2017-05-25 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-25 10:00:00","ga:users":"8.00"},{"ga:date":"2017-05-29 10:00:00","ga:users":"4.00"},{"ga:date":"2017-05-29 15:00:00","ga:users":"2.00"},{"ga:date":"2017-05-30 10:00:00","ga:users":"16.00"},{"ga:date":"2017-05-31 09:00:00","ga:users":"6.00"},{"ga:date":"2017-05-31 10:00:00","ga:users":"4.00"},{"ga:date":"2017-06-01 09:00:00","ga:users":"27.00"},{"ga:date":"2017-06-13 20:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 07:00:00","ga:users":"4.00"},{"ga:date":"2017-06-15 17:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 21:00:00","ga:users":"1.00"},{"ga:date":"2017-06-16 10:00:00","ga:users":"2.00"},{"ga:date":"2017-06-16 14:00:00","ga:users":"4.00"},{"ga:date":"2017-06-16 15:00:00","ga:users":"1.00"},{"ga:date":"2017-05-22 13:00:00","ga:users":"28.00"},{"ga:date":"2017-05-22 14:00:00","ga:users":"5.00"},{"ga:date":"2017-05-22 22:00:00","ga:users":"37.00"},{"ga:date":"2017-05-23 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-23 10:00:00","ga:users":"130.00"},{"ga:date":"2017-05-23 16:00:00","ga:users":"6.00"},{"ga:date":"2017-05-24 16:00:00","ga:users":"32.00"},{"ga:date":"2017-05-25 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-25 10:00:00","ga:users":"8.00"},{"ga:date":"2017-05-29 10:00:00","ga:users":"4.00"},{"ga:date":"2017-05-29 15:00:00","ga:users":"2.00"},{"ga:date":"2017-05-30 10:00:00","ga:users":"16.00"},{"ga:date":"2017-05-31 09:00:00","ga:users":"6.00"},{"ga:date":"2017-05-31 10:00:00","ga:users":"4.00"},{"ga:date":"2017-06-01 09:00:00","ga:users":"27.00"},{"ga:date":"2017-06-13 20:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 07:00:00","ga:users":"4.00"},{"ga:date":"2017-06-15 17:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 21:00:00","ga:users":"1.00"},{"ga:date":"2017-06-16 10:00:00","ga:users":"2.00"}]')
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[{"ga:date":"2017-05-22 13:00:00","ga:users":"28.00"},{"ga:date":"2017-05-22 14:00:00","ga:users":"5.00"},{"ga:date":"2017-05-22 22:00:00","ga:users":"37.00"},{"ga:date":"2017-05-23 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-23 10:00:00","ga:users":"130.00"},{"ga:date":"2017-05-23 16:00:00","ga:users":"6.00"},{"ga:date":"2017-05-24 16:00:00","ga:users":"32.00"},{"ga:date":"2017-05-25 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-25 10:00:00","ga:users":"8.00"},{"ga:date":"2017-05-29 10:00:00","ga:users":"4.00"},{"ga:date":"2017-05-29 15:00:00","ga:users":"2.00"},{"ga:date":"2017-05-30 10:00:00","ga:users":"16.00"},{"ga:date":"2017-05-31 09:00:00","ga:users":"6.00"},{"ga:date":"2017-05-31 10:00:00","ga:users":"4.00"},{"ga:date":"2017-06-01 09:00:00","ga:users":"27.00"},{"ga:date":"2017-06-13 20:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 07:00:00","ga:users":"4.00"},{"ga:date":"2017-06-15 17:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 21:00:00","ga:users":"1.00"},{"ga:date":"2017-06-16 10:00:00","ga:users":"2.00"},{"ga:date":"2017-06-16 14:00:00","ga:users":"4.00"},{"ga:date":"2017-06-16 15:00:00","ga:users":"1.00"},{"ga:date":"2017-05-22 13:00:00","ga:users":"28.00"},{"ga:date":"2017-05-22 14:00:00","ga:users":"5.00"},{"ga:date":"2017-05-22 22:00:00","ga:users":"37.00"},{"ga:date":"2017-05-23 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-23 10:00:00","ga:users":"130.00"},{"ga:date":"2017-05-23 16:00:00","ga:users":"6.00"},{"ga:date":"2017-05-24 16:00:00","ga:users":"32.00"},{"ga:date":"2017-05-25 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-25 10:00:00","ga:users":"8.00"},{"ga:date":"2017-05-29 10:00:00","ga:users":"4.00"},{"ga:date":"2017-05-29 15:00:00","ga:users":"2.00"},{"ga:date":"2017-05-30 10:00:00","ga:users":"16.00"},{"ga:date":"2017-05-31 09:00:00","ga:users":"6.00"},{"ga:date":"2017-05-31 10:00:00","ga:users":"4.00"},{"ga:date":"2017-06-01 09:00:00","ga:users":"27.00"},{"ga:date":"2017-06-13 20:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 07:00:00","ga:users":"4.00"},{"ga:date":"2017-06-15 17:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 21:00:00","ga:users":"1.00"},{"ga:date":"2017-06-16 10:00:00","ga:users":"2.00"},{"ga:date":"2017-06-16 14:00:00","ga:users":"4.00"},{"ga:date":"2017-06-16 15:00:00","ga:users":"1.00"},{"ga:date":"2017-05-22 13:00:00","ga:users":"28.00"},{"ga:date":"2017-05-22 14:00:00","ga:users":"5.00"},{"ga:date":"2017-05-22 22:00:00","ga:users":"37.00"},{"ga:date":"2017-05-23 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-23 10:00:00","ga:users":"130.00"},{"ga:date":"2017-05-23 16:00:00","ga:users":"6.00"},{"ga:date":"2017-05-24 16:00:00","ga:users":"32.00"},{"ga:date":"2017-05-25 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-25 10:00:00","ga:users":"8.00"},{"ga:date":"2017-05-29 10:00:00","ga:users":"4.00"},{"ga:date":"2017-05-29 15:00:00","ga:users":"2.00"},{"ga:date":"2017-05-30 10:00:00","ga:users":"16.00"},{"ga:date":"2017-05-31 09:00:00","ga:users":"6.00"},{"ga:date":"2017-05-31 10:00:00","ga:users":"4.00"},{"ga:date":"2017-06-01 09:00:00","ga:users":"27.00"},{"ga:date":"2017-06-13 20:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 07:00:00","ga:users":"4.00"},{"ga:date":"2017-06-15 17:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 21:00:00","ga:users":"1.00"},{"ga:date":"2017-06-16 10:00:00","ga:users":"2.00"},{"ga:date":"2017-06-16 14:00:00","ga:users":"4.00"},{"ga:date":"2017-06-16 15:00:00","ga:users":"1.00"},{"ga:date":"2017-05-22 13:00:00","ga:users":"28.00"},{"ga:date":"2017-05-22 14:00:00","ga:users":"5.00"},{"ga:date":"2017-05-22 22:00:00","ga:users":"37.00"},{"ga:date":"2017-05-23 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-23 10:00:00","ga:users":"130.00"},{"ga:date":"2017-05-23 16:00:00","ga:users":"6.00"},{"ga:date":"2017-05-24 16:00:00","ga:users":"32.00"},{"ga:date":"2017-05-25 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-25 10:00:00","ga:users":"8.00"},{"ga:date":"2017-05-29 10:00:00","ga:users":"4.00"},{"ga:date":"2017-05-29 15:00:00","ga:users":"2.00"},{"ga:date":"2017-05-30 10:00:00","ga:users":"16.00"},{"ga:date":"2017-05-31 09:00:00","ga:users":"6.00"},{"ga:date":"2017-05-31 10:00:00","ga:users":"4.00"},{"ga:date":"2017-06-01 09:00:00","ga:users":"27.00"},{"ga:date":"2017-06-13 20:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 07:00:00","ga:users":"4.00"},{"ga:date":"2017-06-15 17:00:00","ga:users":"2.00"},{"ga:date":"2017-06-15 21:00:00","ga:users":"1.00"},{"ga:date":"2017-06-16 10:00:00","ga:users":"2.00"}]
asd<-jsonlite::fromJson('[{"ga:date":"2017-06-03 00:00:00","ga:users":"11.00"},
{"ga:date":"2017-06-03 01:00:00","ga:users":"11.00"},
{"ga:date":"2017-06-03 02:00:00","ga:users":"10.00"},
{"ga:date":"2017-06-03 03:00:00","ga:users":"4.00"},
{"ga:date":"2017-06-03 04:00:00","ga:users":"5.00"},
{"ga:date":"2017-06-03 06:00:00","ga:users":"2.00"},
{"ga:date":"2017-06-03 07:00:00","ga:users":"12.00"},
{"ga:date":"2017-06-03 08:00:00","ga:users":"16.00"},
{"ga:date":"2017-06-03 09:00:00","ga:users":"43.00"}]'')
asd<-jsonlite::fromJson('[{"ga:date":"2017-06-03 00:00:00","ga:users":"11.00"},
{"ga:date":"2017-06-03 01:00:00","ga:users":"11.00"},
{"ga:date":"2017-06-03 02:00:00","ga:users":"10.00"},
{"ga:date":"2017-06-03 03:00:00","ga:users":"4.00"},
{"ga:date":"2017-06-03 04:00:00","ga:users":"5.00"},
{"ga:date":"2017-06-03 06:00:00","ga:users":"2.00"},
{"ga:date":"2017-06-03 07:00:00","ga:users":"12.00"},
{"ga:date":"2017-06-03 08:00:00","ga:users":"16.00"},
{"ga:date":"2017-06-03 09:00:00","ga:users":"43.00"}]')
asd<-jsonlite::fromJSON('[{"ga:date":"2017-06-03 00:00:00","ga:users":"11.00"},
{"ga:date":"2017-06-03 01:00:00","ga:users":"11.00"},
{"ga:date":"2017-06-03 02:00:00","ga:users":"10.00"},
{"ga:date":"2017-06-03 03:00:00","ga:users":"4.00"},
{"ga:date":"2017-06-03 04:00:00","ga:users":"5.00"},
{"ga:date":"2017-06-03 06:00:00","ga:users":"2.00"},
{"ga:date":"2017-06-03 07:00:00","ga:users":"12.00"},
{"ga:date":"2017-06-03 08:00:00","ga:users":"16.00"},
{"ga:date":"2017-06-03 09:00:00","ga:users":"43.00"}]')
asd
tsoutlier::algorithm(asd)
asd<-jsonlite::fromJSON('[{"ga:date":"2017-06-10 09:00:00","ga:users":"1.00"},{"ga:date":"2017-06-11 07:00:00","ga:users":"1.00"},{"ga:date":"2017-06-11 23:00:00","ga:users":"1.00"}]')
asd
tsoutlier::algorithm(asd)
tsoutliers::tso(asd)
asd
tsoutlier::algorithm(asd)
asd->input
input[,2]<-as.numeric(input[,2])
dat<-input
dat
if(nchar(dat[,1][1])>10){
seq_len<-nrow(dat)
input[,1]<-seq(as.Date("2000/1/1"), by = "day", length.out = seq_len)
input[,1]<-as.Date(as.character(input[,1]), format='%Y-%m-%d')
dat[,1]<-as.POSIXct(dat[,1])
}else {
input[,1]<-as.Date(as.character(input[,1]), format='%Y-%m-%d')
input<-input[order(input[,1]),]
dat[,1]<-as.Date(as.character(dat[,1]), format='%Y-%m-%d')
dat<-dat[order(dat[,1]),]
}
input
t_c<- timeseries_conversion(input[,2], order.by=input[,1])
tsm<-timeseries(t_c)
tsm
indx <- 1:length(dat[,1])
var.use <- dat[,2]
dat
temp<-var.use
result<-tso(tsm)
result<-tsoutliers::tso(tsm)
analysis<-outlier_detection(tsm,maxit.iloop = 1)
input$`ga:users`<-1:3
t_c<- timeseries_conversion(input[,2], order.by=input[,1])
tsm<-timeseries(t_c)
indx <- 1:length(dat[,1])
var.use <- dat[,2]
temp<-var.use
result<-tso(tsm)
analysis<-outlier_detection(tsm,maxit.iloop = 1)
y=tsm; xreg = NULL; cval = NULL; delta = 0.7; n.start = 50;
types = c("AO", "LS", "TC"); # c("IO", "AO", "LS", "TC", "SLS")
maxit = 1; maxit.iloop = 4; cval.reduce = 0.14286;
remove.method = c("en-masse", "bottom-up");
remove.cval = NULL;
tsmethod = c("auto.arima", "arima", "stsm"),
args.tsmethod = NULL; args.tsmodel = NULL; logfile = NULL
y=tsm; xreg = NULL; cval = NULL; delta = 0.7; n.start = 50;
types = c("AO", "LS", "TC"); # c("IO", "AO", "LS", "TC", "SLS")
maxit = 1; maxit.iloop = 4; cval.reduce = 0.14286;
remove.method = c("en-masse", "bottom-up");
remove.cval = NULL;
tsmethod = c("auto.arima", "arima", "stsm");
args.tsmethod = NULL; args.tsmodel = NULL; logfile = NULL
tsmethod <- match.arg(tsmethod)
remove.method <- match.arg(remove.method)
attr.y <- attributes(y)
n <- length(y)
yname <- deparse(substitute(y))
asd<-jsonlite::fromJSON('[{"ga:date":"2017-06-10 09:00:00","ga:users":"1.00"},{"ga:date":"2017-06-11 07:00:00","ga:users":"1.00"},{"ga:date":"2017-06-11 23:00:00","ga:users":"1.00"},{"ga:date":"2017-05-22 14:00:00","ga:users":"5.00"},{"ga:date":"2017-05-22 22:00:00","ga:users":"37.00"},{"ga:date":"2017-05-23 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-23 10:00:00","ga:users":"130.00"},{"ga:date":"2017-05-23 16:00:00","ga:users":"6.00"},{"ga:date":"2017-05-24 16:00:00","ga:users":"32.00"},{"ga:date":"2017-05-25 09:00:00","ga:users":"9.00"}]')
asd
algorithm(asd)
tsoutlier::algorithm(asd)
asd<-jsonlite::fromJSON('[{"ga:date":"2017-06-10 09:00:00","ga:users":"1.00"},{"ga:date":"2017-06-11 07:00:00","ga:users":"1.00"},{"ga:date":"2017-06-11 23:00:00","ga:users":"1.00"},{"ga:date":"2017-05-22 14:00:00","ga:users":"5.00"},{"ga:date":"2017-05-22 22:00:00","ga:users":"37.00"},{"ga:date":"2017-05-23 09:00:00","ga:users":"9.00"},{"ga:date":"2017-05-23 10:00:00","ga:users":"130.00"},{"ga:date":"2017-05-23 16:00:00","ga:users":"6.00"},{"ga:date":"2017-05-24 16:00:00","ga:users":"32.00"},{"ga:date":"2017-05-25 09:00:00","ga:users":"9.00"}]')
asd
tsoutlier::algorithm(asd[1:3,])
tsoutlier::algorithm(asd[1:4,])
tsoutlier::algorithm(asd[2:4,])
tsoutlier::algorithm(asd[5:7,])
asd$`ga:users`=0
tsoutlier::algorithm(asd[5:7,])
tsoutlier::algorithm(asd)
library(tsoutlier)
asd<-jsonlite::toJSON("[{"ga:date":"2017-05-27","ga:users":"48.63"},{"ga:date":"2017-05-28","ga:users":"41.58"},{"ga:date":"2017-05-29","ga:users":"46.02"},{"ga:date":"2017-05-30","ga:users":"48.80"},{"ga:date":"2017-05-31","ga:users":"53.72"},{"ga:date":"2017-06-01","ga:users":"47.20"},{"ga:date":"2017-06-02","ga:users":"46.04"},{"ga:date":"2017-06-03","ga:users":"57.92"},{"ga:date":"2017-06-04","ga:users":"56.85"},{"ga:date":"2017-06-05","ga:users":"53.57"},{"ga:date":"2017-06-06","ga:users":"66.35"},{"ga:date":"2017-06-07","ga:users":"46.66"},{"ga:date":"2017-06-08","ga:users":"45.18"},{"ga:date":"2017-06-09","ga:users":"49.13"},{"ga:date":"2017-06-10","ga:users":"47.21"},{"ga:date":"2017-06-11","ga:users":"50.89"},{"ga:date":"2017-06-12","ga:users":"47.18"},{"ga:date":"2017-06-13","ga:users":"44.59"},{"ga:date":"2017-06-14","ga:users":"49.99"},{"ga:date":"2017-06-15","ga:users":"50.37"},{"ga:date":"2017-06-16","ga:users":"49.92"},{"ga:date":"2017-06-17","ga:users":"41.73"},{"ga:date":"2017-06-18","ga:users":"45.52"},{"ga:date":"2017-06-19","ga:users":"56.61"},{"ga:date":"2017-06-20","ga:users":"49.77"},{"ga:date":"2017-06-21","ga:users":"46.13"},{"ga:date":"2017-06-22","ga:users":"46.14"},{"ga:date":"2017-06-23","ga:users":"47.10"},{"ga:date":"2017-06-24","ga:users":"47.19"},{"ga:date":"2017-06-25","ga:users":"43.66"},{"ga:date":"2017-06-26","ga:users":"44.91"},{"ga:date":"2017-06-27","ga:users":"62.07"},{"ga:date":"2017-06-28","ga:users":"53.14"}]")
asd<-jsonlite:fromJSON("[{"ga:date":"2017-05-27","ga:users":"48.63"},{"ga:date":"2017-05-28","ga:users":"41.58"},{"ga:date":"2017-05-29","ga:users":"46.02"},{"ga:date":"2017-05-30","ga:users":"48.80"},{"ga:date":"2017-05-31","ga:users":"53.72"},{"ga:date":"2017-06-01","ga:users":"47.20"},{"ga:date":"2017-06-02","ga:users":"46.04"},{"ga:date":"2017-06-03","ga:users":"57.92"},{"ga:date":"2017-06-04","ga:users":"56.85"},{"ga:date":"2017-06-05","ga:users":"53.57"},{"ga:date":"2017-06-06","ga:users":"66.35"},{"ga:date":"2017-06-07","ga:users":"46.66"},{"ga:date":"2017-06-08","ga:users":"45.18"},{"ga:date":"2017-06-09","ga:users":"49.13"},{"ga:date":"2017-06-10","ga:users":"47.21"},{"ga:date":"2017-06-11","ga:users":"50.89"},{"ga:date":"2017-06-12","ga:users":"47.18"},{"ga:date":"2017-06-13","ga:users":"44.59"},{"ga:date":"2017-06-14","ga:users":"49.99"},{"ga:date":"2017-06-15","ga:users":"50.37"},{"ga:date":"2017-06-16","ga:users":"49.92"},{"ga:date":"2017-06-17","ga:users":"41.73"},{"ga:date":"2017-06-18","ga:users":"45.52"},{"ga:date":"2017-06-19","ga:users":"56.61"},{"ga:date":"2017-06-20","ga:users":"49.77"},{"ga:date":"2017-06-21","ga:users":"46.13"},{"ga:date":"2017-06-22","ga:users":"46.14"},{"ga:date":"2017-06-23","ga:users":"47.10"},{"ga:date":"2017-06-24","ga:users":"47.19"},{"ga:date":"2017-06-25","ga:users":"43.66"},{"ga:date":"2017-06-26","ga:users":"44.91"},{"ga:date":"2017-06-27","ga:users":"62.07"},{"ga:date":"2017-06-28","ga:users":"53.14"}]")
asd<-jsonlite:fromJSON('[{"ga:date":"2017-05-27","ga:users":"48.63"},{"ga:date":"2017-05-28","ga:users":"41.58"},{"ga:date":"2017-05-29","ga:users":"46.02"},{"ga:date":"2017-05-30","ga:users":"48.80"},{"ga:date":"2017-05-31","ga:users":"53.72"},{"ga:date":"2017-06-01","ga:users":"47.20"},{"ga:date":"2017-06-02","ga:users":"46.04"},{"ga:date":"2017-06-03","ga:users":"57.92"},{"ga:date":"2017-06-04","ga:users":"56.85"},{"ga:date":"2017-06-05","ga:users":"53.57"},{"ga:date":"2017-06-06","ga:users":"66.35"},{"ga:date":"2017-06-07","ga:users":"46.66"},{"ga:date":"2017-06-08","ga:users":"45.18"},{"ga:date":"2017-06-09","ga:users":"49.13"},{"ga:date":"2017-06-10","ga:users":"47.21"},{"ga:date":"2017-06-11","ga:users":"50.89"},{"ga:date":"2017-06-12","ga:users":"47.18"},{"ga:date":"2017-06-13","ga:users":"44.59"},{"ga:date":"2017-06-14","ga:users":"49.99"},{"ga:date":"2017-06-15","ga:users":"50.37"},{"ga:date":"2017-06-16","ga:users":"49.92"},{"ga:date":"2017-06-17","ga:users":"41.73"},{"ga:date":"2017-06-18","ga:users":"45.52"},{"ga:date":"2017-06-19","ga:users":"56.61"},{"ga:date":"2017-06-20","ga:users":"49.77"},{"ga:date":"2017-06-21","ga:users":"46.13"},{"ga:date":"2017-06-22","ga:users":"46.14"},{"ga:date":"2017-06-23","ga:users":"47.10"},{"ga:date":"2017-06-24","ga:users":"47.19"},{"ga:date":"2017-06-25","ga:users":"43.66"},{"ga:date":"2017-06-26","ga:users":"44.91"},{"ga:date":"2017-06-27","ga:users":"62.07"},{"ga:date":"2017-06-28","ga:users":"53.14"}]')
asd<-jsonlite::fromJSON('[{"ga:date":"2017-05-27","ga:users":"48.63"},{"ga:date":"2017-05-28","ga:users":"41.58"},{"ga:date":"2017-05-29","ga:users":"46.02"},{"ga:date":"2017-05-30","ga:users":"48.80"},{"ga:date":"2017-05-31","ga:users":"53.72"},{"ga:date":"2017-06-01","ga:users":"47.20"},{"ga:date":"2017-06-02","ga:users":"46.04"},{"ga:date":"2017-06-03","ga:users":"57.92"},{"ga:date":"2017-06-04","ga:users":"56.85"},{"ga:date":"2017-06-05","ga:users":"53.57"},{"ga:date":"2017-06-06","ga:users":"66.35"},{"ga:date":"2017-06-07","ga:users":"46.66"},{"ga:date":"2017-06-08","ga:users":"45.18"},{"ga:date":"2017-06-09","ga:users":"49.13"},{"ga:date":"2017-06-10","ga:users":"47.21"},{"ga:date":"2017-06-11","ga:users":"50.89"},{"ga:date":"2017-06-12","ga:users":"47.18"},{"ga:date":"2017-06-13","ga:users":"44.59"},{"ga:date":"2017-06-14","ga:users":"49.99"},{"ga:date":"2017-06-15","ga:users":"50.37"},{"ga:date":"2017-06-16","ga:users":"49.92"},{"ga:date":"2017-06-17","ga:users":"41.73"},{"ga:date":"2017-06-18","ga:users":"45.52"},{"ga:date":"2017-06-19","ga:users":"56.61"},{"ga:date":"2017-06-20","ga:users":"49.77"},{"ga:date":"2017-06-21","ga:users":"46.13"},{"ga:date":"2017-06-22","ga:users":"46.14"},{"ga:date":"2017-06-23","ga:users":"47.10"},{"ga:date":"2017-06-24","ga:users":"47.19"},{"ga:date":"2017-06-25","ga:users":"43.66"},{"ga:date":"2017-06-26","ga:users":"44.91"},{"ga:date":"2017-06-27","ga:users":"62.07"},{"ga:date":"2017-06-28","ga:users":"53.14"}]')
asd
tsoutlier::algorithm(asd)
asdf<-tsoutlier::algorithm(asd)
View(asdf)
write.csv(asdf,"/Users/kartikeya kirar/Desktop/asdf.txt")
input<-asd
options(warn=-1)
input[,2]<-as.numeric(input[,2])
dat<-input
if(nchar(dat[,1][1])>10){
seq_len<-nrow(dat)
input[,1]<-seq(as.Date("2000/1/1"), by = "day", length.out = seq_len)
input[,1]<-as.Date(as.character(input[,1]), format='%Y-%m-%d')
dat[,1]<-as.POSIXct(dat[,1])
}else {
input[,1]<-as.Date(as.character(input[,1]), format='%Y-%m-%d')
input<-input[order(input[,1]),]
dat[,1]<-as.Date(as.character(dat[,1]), format='%Y-%m-%d')
dat<-dat[order(dat[,1]),]
}
t_c<- timeseries_conversion(input[,2], order.by=input[,1])
tsm<-timeseries(t_c)
input
indx <- 1:length(dat[,1])
var.use <- dat[,2]
temp<-var.use
result<-tso(tsm)
result<-tsoutliers::tso(tsm)
analysis<-result$outliers
analysis
lo <- loess(result$yadj~indx)
predicted<-predict(lo)
dat[,2][result$times]<-result$yadj[result$times]
result$yadj[result$times]
result$yadj
outlier<-list()
outlier[1:length(dat[,1])]<-0
outlier[analysis$ind]<-1
raw_limit<-sum(abs(var.use-dat[,2])/var.use)/length(result$times)
raw_limit
abs(var.use-dat[,2])
limit<-raw_limit*0.5
chk<-unique((var.use-dat[,2])/var.use)[-1]
chk
sum(chk<limit)
limit
if(sum(chk<limit)==0){
limit_s<-limit*0.5
} else{
limit<-limit*0.75
limit_s<-limit*0.5
}
if(sum(chk<limit)!=0){
limit<-limit*0.75
limit_s<-limit*0.75
}
limit_s