variable "fitted" not ordered after using prediction for plm model

[BuenosDiazMatthias]

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• a possible bug
• a question about package functionality
• a suggested code or documentation change, improvement to the code, or feature request

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Put your code here:

###Description of data and problem: data is artifical and enough for problem description,
### it describes something over different IDs and time (panel). 
###After estimation (package plm, pooling, for simplicity using only a lag of endogen. variable)
### I used prediction package to forecast one ahead (t+n) in time. Results (variable "fitted") of this prediction is correct but not in the right order of the panel: a first forecasted value refers to the first ID but not to t+1, second value belongs to (ID2,t+1) and not ID1, t+1), third value belongs to ID3,t+1 (and not to ID1,t+3) and so on. To sum up: data for "fitted" is sorted by ID first and not for ID and time. Please correct. Thany you!
## load package
library("prediction")
library(plm)
## code goes here
library(prediction)
library(plm)
library(readxl)
library(panelr)
library(stargazer)

#load data,  note the last 5 observations for each ID are n.a. to make predictions
panel1<-read_excel("C:/your_place/test1.xlsx")

#declare pabel structure
panel1<-pdata.frame(panel1, index=c("ID","time"))
panel1$time <- as.Date(as.character(panel1$time), format = "%Y")

#estimate model
pooled_p1 <- plm(Y~lag(Y), panel1, model="pooling") 

#checking results for making pocket calculator predictions
stargazer(pooled_p1, type="text", title="Lag1", digits=2, column.labels = c("Pooled"))

#making predictions
      #making a subsample to predict
 
        panel1_sub<-subset(panel1,time>="0017-05-19") #you have to update month and day to actual date!
        
  Forecast_pooled_p1<-prediction(pooled_p1, data = panel1_sub)
  
#check the data

## session info for your system
sessionInfo()

test1.xlsx