prodest package in R, TFP growth estimation

I have a question regarding the results and its transformations received from prodest package estimation. So, the dataset is available here https://drive.google.com/file/d/1aedWYABus1fQjKWxkOmYOmxv-qSja7hF/view?usp=sharing. My code is the following:

remove(list=ls())

library(plm)
library(dplyr)
library(ggplot2)
library(prodest)
library(estprod)
library(broom)
library(pdynmc)

pckg<-c("plm","readxl","dplyr","ggplot2", "broom","prodest", "estprod")
install.packages(c("plm","readxl","dplyr","ggplot2", "broom","prodest", "estprod"))
lapply(pckg, require, character.only = TRUE)

# Set the working directory
setwd("C:/Users/vadya/Desktop/baka")

# Downloading the survey data
Data <- read.csv("LV.csv", header=TRUE, sep=",")
str(Data)

Data$ID<-as.numeric(as.factor(Data$ID))

summary(Data)

# Creating a panel data frame
PData <- pdata.frame(Data, index = c("ID","Year"))

pdim(PData)
pvar(PData)

DataA <- Data %>% 
  filter(NACE == 'A' & Year < 2014) %>% 
  filter(VA > 0, L > 0, K > 0, M > 0) %>%
  select(ID, Year, L, VA, K, M) %>% 
  summarise(ID = ID,
            Year = Year,
            l = log(L),
            va = log(VA),
            k = log(K),
            m = log(M))
  
####################################################################################################################################
mod2LP <- prodest::prodestLP(DataA$va, fX = DataA$l, sX = DataA$k, pX = DataA$m, idvar = DataA$ID, timevar = DataA$Year, 
                             R = 100, cX = NULL, opt = "optim", theta0 = NULL, cluster = NULL, tol = 1e-100, exit = FALSE)  
mod2LP
omegaLP <- prodest::omega(mod2LP)
summary(mod2LP)
summary(omegaLP)



mod2OP <- prodest::prodestOP(DataA$va, fX = DataA$l, sX = DataA$k, pX = DataA$m, idvar = DataA$ID, timevar = DataA$Year, 
                             R = 100, cX = NULL, opt = "optim", theta0 = NULL, cluster = NULL, tol = 1e-100, exit = FALSE)  

mod2OP
omegaOP <- prodest::omega(mod2OP)
summary(mod2OP)
summary(omegaOP)



mod2ACF <-  prodest::prodestACF(DataA$va, fX = DataA$l, sX = DataA$k, pX = DataA$m, idvar = DataA$ID, timevar = DataA$Year, 
                                R = 100, cX = NULL, opt = 'optim', theta0 = NULL, cluster = NULL)  

mod2ACF
omegaACF <- prodest::omega(mod2ACF)
summary(mod2ACF)
summary(omegaACF)



mod2W <-  prodest::prodestWRDG_GMM(DataA$va, fX = DataA$l, sX = DataA$k, pX = DataA$m, idvar = DataA$ID, timevar = DataA$Year, 
                                   cX = NULL, tol = 1e-100)  
mod2W
omegaW <- prodest::omega(mod2W)
summary(mod2W)
summary(omegaW)

####################################################################################################################################

After using the omega function I receive the summary statistics of the TFP estimation. However, if I want to assign this omega function output to another object, I end up with matrix of randomly assigned numbers (I guess so). Hence, the problem is that my dataset is from 2011 till 2019, and I need to get the change of the TFP YoY or, basically the growth of it for each entity separately YoY. Would really much appreciate your suggestions since I tried a lot of things (including changing the overall function prodest in order to get the TFP assigned to each firm in each year, but nothing really helped).