diff --git a/tests/testthat/test_pmml.ARIMA.R b/tests/testthat/test_pmml.ARIMA.R
index 80ff42e..354b409 100644
--- a/tests/testthat/test_pmml.ARIMA.R
+++ b/tests/testthat/test_pmml.ARIMA.R
@@ -5,6 +5,21 @@ data("WWWusage")
 data("AirPassengers")
 data("JohnsonJohnson")
 
+text_to_num_list <- function(xml_element) {
+  # Convert string that contains a list of numbers to a list of numbers
+  aa <- xmlToList(xml_element)
+  cc <- strsplit(aa, split = " ", fixed = TRUE)[[1]]
+  dd <- as.numeric(cc)
+}
+
+expect_equal_ttnl <- function(xml_element, current){
+  expect_equal(text_to_num_list(xml_element), current, tolerance = 1e-2)
+}
+
+expect_equal_num <- function(target, current) {
+  expect_equal(as.numeric(target), current, tolerance = 1e-2)
+}
+
 
 test_that("DataDictionary node contains expected elements", {
   fit_2 <- auto.arima(WWWusage)
@@ -39,22 +54,17 @@ test_that("NonseasonalComponent node contains required elements 1", {
   expect_equal(xmlGetAttr(p_fit_5[[3]][[4]][[1]], name = "q"), 1)
 
   # AR component
-  expect_equal(
-    toString(p_fit_5[[3]][[4]][[1]][[1]][[1]][[1]]),
-    "-0.196933688666896 0.0882676656284808 0.9429079310464"
-  )
+  expect_equal_ttnl(p_fit_5[[3]][[4]][[1]][[1]][[1]][[1]],
+                    c(-0.19693368896618, 0.0882676656284808, 0.9429079310464))
+  
+  
+  # MA component - MACoefficients
+  expect_equal_ttnl(p_fit_5[[3]][[4]][[1]][[2]][[1]][[1]][[1]],0.999467612244043)
 
-  # MA component - MACoefficients; sign of coefficients in PMML is opposite to R
-  expect_equal(
-    toString(p_fit_5[[3]][[4]][[1]][[2]][[1]][[1]]),
-    "<Array type=\"real\" n=\"1\">0.999467612244043</Array>"
-  )
 
   # MA component - Residuals
-  expect_equal(
-    toString(p_fit_5[[3]][[4]][[1]][[2]][[2]]),
-    "<Residuals>\n <Array type=\"real\" n=\"1\">-846.776313143145</Array>\n</Residuals>"
-  )
+  expect_equal_ttnl(p_fit_5[[3]][[4]][[1]][[2]][[2]][[1]][[1]],-846.776313143145)
+  
 })
 
 test_that("non-seasonal ARIMA node contains correct attributes", {
@@ -62,9 +72,9 @@ test_that("non-seasonal ARIMA node contains correct attributes", {
   fit_6 <- Arima(s, order = c(0, 0, 1))
   p_fit_6 <- pmml(fit_6)
 
-  expect_equal(xmlGetAttr(p_fit_6[[3]][[4]], name = "RMSE"), "3472.72443700833")
+  expect_equal_num(xmlGetAttr(p_fit_6[[3]][[4]], name = "RMSE"), 3472.72443700833)
   expect_equal(xmlGetAttr(p_fit_6[[3]][[4]], name = "transformation"), "none")
-  expect_equal(xmlGetAttr(p_fit_6[[3]][[4]], name = "constantTerm"), "10327.6226360507")
+  expect_equal_num(xmlGetAttr(p_fit_6[[3]][[4]], name = "constantTerm"), 10327.6226360507)
   expect_equal(xmlGetAttr(p_fit_6[[3]][[4]], name = "predictionMethod"), "conditionalLeastSquares")
 })
 
@@ -82,12 +92,13 @@ test_that("seasonal ARIMA model contains correct elements 1", {
   expect_equal(xmlGetAttr(p_fit_7[[3]][[4]][[2]], name = "Q"), 1)
   expect_equal(xmlGetAttr(p_fit_7[[3]][[4]][[2]], name = "period"), 4)
 
-  expect_equal(toString(p_fit_7[[3]][[4]][[2]][[1]][[1]][[1]]), '<Array type="real" n="1">0.999999926590528</Array>')
+  expect_equal_ttnl(p_fit_7[[3]][[4]][[2]][[1]][[1]][[1]][[1]], 0.999999926590528)
+  
   # Seasonal residuals array should have 6 elements.
-  expect_equal(
-    toString(p_fit_7[[3]][[4]][[2]][[1]][[2]][[1]]),
-    '<Array type="real" n="6">0.840294788225463 1.79540974711022 3.43600813764863 0.595257922098859 1.560371580367 1.33444221515274</Array>'
-  )
+  expect_equal_ttnl(p_fit_7[[3]][[4]][[2]][[1]][[2]][[1]][[1]],
+                    c(0.840294788225463, 1.79540974711022, 3.43600813764863, 
+                      0.595257922098859, 1.560371580367, 1.33444221515274))
+  
 })
 
 test_that("seasonal ARIMA model contains correct elements 2", {
@@ -104,11 +115,13 @@ test_that("seasonal ARIMA model contains correct elements 2", {
   expect_equal(xmlGetAttr(p_fit_8[[3]][[4]][[2]], name = "Q"), 1)
   expect_equal(xmlGetAttr(p_fit_8[[3]][[4]][[2]], name = "period"), 12)
 
-  expect_equal(toString(p_fit_8[[3]][[4]][[2]][[1]][[1]]), '<Array type="real" n="1">-0.926970851026725</Array>')
+  expect_equal_ttnl(p_fit_8[[3]][[4]][[2]][[1]][[1]][[1]], -0.926970851026725)
   # Seasonal residuals array should have 13 elements.
-  expect_equal(
-    toString(p_fit_8[[3]][[4]][[2]][[2]][[2]][[1]]),
-    '<Array type="real" n="13">16.6406514721613 -2.15049966299974 -8.78471974960152 -34.7165557860653 42.1922537998818 2.72016048914321 5.57048733936438 14.8646481189408 -23.3767800799817 -7.00132283870703 5.56068703039644 -24.4368048030507 -7.86142188676456</Array>'
+  expect_equal_ttnl(p_fit_8[[3]][[4]][[2]][[2]][[2]][[1]][[1]],
+    c(16.6406514721613, -2.15049966299974, -8.78471974960152, -34.7165557860653,
+      42.1922537998818, 2.72016048914321, 5.57048733936438, 14.8646481189408,
+      -23.3767800799817, -7.00132283870703, 5.56068703039644, -24.4368048030507,
+      -7.86142188676456)
   )
 })
 
@@ -117,7 +130,7 @@ test_that("seasonal ARIMA model contains correct elements 3", {
   fit_9 <- Arima(AirPassengers, order = c(1, 2, 3), seasonal = c(1, 2, 1))
   p_fit_9 <- pmml(fit_9)
 
-  expect_equal(xmlGetAttr(p_fit_9[[3]][[4]], name = "constantTerm"), "0")
+  expect_equal_num(xmlGetAttr(p_fit_9[[3]][[4]], name = "constantTerm"), 0)
 
   expect_equal(xmlGetAttr(p_fit_9[[3]][[4]][[1]], name = "p"), 1)
   expect_equal(xmlGetAttr(p_fit_9[[3]][[4]][[1]], name = "d"), 2)
@@ -129,25 +142,25 @@ test_that("seasonal ARIMA model contains correct elements 3", {
   expect_equal(xmlGetAttr(p_fit_9[[3]][[4]][[2]], name = "period"), 12)
 
   # NonseasonalComponent coefficients
-  expect_equal(toString(p_fit_9[[3]][[4]][[1]][[1]][[1]]), '<Array type="real" n="1">-0.918811953411307</Array>')
-  expect_equal(toString(p_fit_9[[3]][[4]][[1]][[2]][[1]][[1]]), '<Array type="real" n="3">-0.488398025152718 -0.981238492527093 0.47123365713457</Array>')
-  expect_equal(toString(p_fit_9[[3]][[4]][[1]][[2]][[2]][[1]]), '<Array type="real" n="3">10.6024485251517 -16.6110095847448 -3.45077032800267</Array>')
+  expect_equal_ttnl(p_fit_9[[3]][[4]][[1]][[1]][[1]][[1]], -0.918811953411307)
+  expect_equal_ttnl(p_fit_9[[3]][[4]][[1]][[2]][[1]][[1]][[1]],
+                    c(-0.488398025152718, -0.981238492527093, 0.47123365713457))
+  expect_equal_ttnl(p_fit_9[[3]][[4]][[1]][[2]][[2]][[1]][[1]],
+                    c(10.6024485251517, -16.6110095847448, -3.45077032800267))
 
   # SeasonalComponent coefficients
-  expect_equal(toString(p_fit_9[[3]][[4]][[2]][[1]][[1]]), '<Array type="real" n="1">-0.33060697133757</Array>')
-  expect_equal(toString(p_fit_9[[3]][[4]][[2]][[2]][[1]][[1]]), '<Array type="real" n="1">-0.964840603841212</Array>')
+  expect_equal_ttnl(p_fit_9[[3]][[4]][[2]][[1]][[1]][[1]], -0.33060697133757)
+  expect_equal_ttnl(p_fit_9[[3]][[4]][[2]][[2]][[1]][[1]][[1]], -0.964840603841212)
   # Seasonal residuals array should have 15 elements.
-  expect_equal(toString(p_fit_9[[3]][[4]][[2]][[2]][[2]][[1]]), '<Array type=\"real\" n=\"15\">-0.231414430272416 7.85449813502021 14.0341170808424 0.488050253167314 -3.47775177064476 -34.7531345572846 36.9803974323111 -0.721770286617552 3.21345471099022 5.83445945385706 -21.7707201166725 -1.21862197305704 10.6024485251517 -16.6110095847448 -3.45077032800267</Array>')
+  expect_equal_ttnl(p_fit_9[[3]][[4]][[2]][[2]][[2]][[1]][[1]],
+               c(-0.231414430272416, 7.85449813502021, 14.0341170808424, 
+                 0.488050253167314, -3.47775177064476, -34.7531345572846, 
+                 36.9803974323111, -0.721770286617552, 3.21345471099022, 5.83445945385706,
+                 -21.7707201166725, -1.21862197305704, 10.6024485251517, -16.6110095847448,
+                 -3.45077032800267))
 })
 
 
-# test_that("seasonal ARIMA model contains correct elements 4", {
-#   fit_9a <- Arima(AirPassengers,order=c(1,1,0),seasonal=c(0,1,1))
-#   p_fit_9a <- pmml(fit_9a)
-#
-# })
-
-
 
 test_that("Seasonal ARIMA without non-seasonal component does not contain NonseasonalComponent", {
   fit_10 <- Arima(AirPassengers, order = c(0, 0, 0), seasonal = c(1, 2, 1))