#======================================================================================================#
#Purpose: Evaluate the Dominick data while providing fewer arguments.
#
# Author: Stefanos Kechagias
# Date: August 2024
#=====================================================================================================#
test_that("LGC wrapper works for evaluation MixPois AR(1)", {
# load libraries
library(optimx)
library(ltsa)
require(countsFun)
library(itsmr)
library(tictoc)
library(devtools)
library(VGAM)
library(iZID)
# load the data
#mysales = read.csv("https://raw.githubusercontent.com/jlivsey/countsFun/master/data/MySelectedSeries.csv")
data(MySelectedSeries)
# attach the dataframe
n = 104
Smallsales = mysales[1:n,]
# regressor variable with intercept
DependentVar = Smallsales$MOVE
Regressor = cbind(rep(1,length(Smallsales$Buy)),Smallsales$Buy)
CountDist = "Negative Binomial"
ARMAModel = c(2,0)
OptMethod = "L-BFGS-B"
initialParam = c(2.1756853 , 1.2048704,0.5, -0.3875602, 0.0603419 )
# call the wrapper function with less arguments
mylgc = lgc(DependentVar = DependentVar,
Regressor = Regressor,
CountDist = CountDist,
ARMAModel = ARMAModel,
OptMethod = OptMethod,
initialParam = initialParam)
expect_equal(mylgc$FitStatistics[[1]], 392.673, tolerance = 10^(-3))
})
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