GNU Octave, version 4.4.0
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>> options = optimset('GradObj', 'on', 'MaxIter', '1
00')
options =

  scalar structure containing the fields:

    GradObj = on
    MaxIter = 100

>> initialTheta = zeros(2,1)
initialTheta =

   0
   0

>> [optTheta, functionVal, exitFlag] = fminunc(@costFunction,initialTheta, options)
error: @costFunction: no function and no method found
>>
>> [optTheta, functionVal, exitFlag] = fminunc(@costFunction,initialTheta, options)
jVal =  50
gradient =

   0
   0

gradient =

  -10
    0

gradient =

  -10
  -10

jVal =  50
gradient =

   0
   0

gradient =

  -10
    0

gradient =

  -10
  -10

jVal =  48.596
gradient =

   0
   0

gradient =

  -9.85858
   0.00000

gradient =

  -9.8586
  -9.8586

jVal =  48.596
gradient =

   0
   0

gradient =

  -9.85858
   0.00000

gradient =

  -9.8586
  -9.8586

jVal =  46.644
gradient =

   0
   0

gradient =

  -9.65858
   0.00000

gradient =

  -9.6586
  -9.6586

jVal =  46.644
gradient =

   0
   0

gradient =

  -9.65858
   0.00000

gradient =

  -9.6586
  -9.6586

jVal =  43.952
gradient =

   0
   0

gradient =

  -9.37574
   0.00000

gradient =

  -9.3757
  -9.3757

jVal =  43.952
gradient =

   0
   0

gradient =

  -9.37574
   0.00000

gradient =

  -9.3757
  -9.3757

jVal =  40.282
gradient =

   0
   0

gradient =

  -8.97575
   0.00000

gradient =

  -8.9758
  -8.9758

jVal =  40.282
gradient =

   0
   0

gradient =

  -8.97575
   0.00000

gradient =

  -8.9758
  -8.9758

jVal =  35.365
gradient =

   0
   0

gradient =

  -8.41009
   0.00000

gradient =

  -8.4101
  -8.4101

jVal =  35.365
gradient =

   0
   0

gradient =

  -8.41009
   0.00000

gradient =

  -8.4101
  -8.4101

jVal =  28.957
gradient =

   0
   0

gradient =

  -7.61013
   0.00000

gradient =

  -7.6101
  -7.6101

jVal =  28.957
gradient =

   0
   0

gradient =

  -7.61013
   0.00000

gradient =

  -7.6101
  -7.6101

jVal =  20.988
gradient =

   0
   0

gradient =

  -6.47882
   0.00000

gradient =

  -6.4788
  -6.4788

jVal =  20.988
gradient =

   0
   0

gradient =

  -6.47882
   0.00000

gradient =

  -6.4788
  -6.4788

jVal =  11.902
gradient =

   0
   0

gradient =

  -4.87893
   0.00000

gradient =

  -4.8789
  -4.8789

jVal =  11.902
gradient =

   0
   0

gradient =

  -4.87893
   0.00000

gradient =

  -4.8789
  -4.8789

jVal =  3.4227
gradient =

   0
   0

gradient =

  -2.61636
   0.00000

gradient =

  -2.6164
  -2.6164

jVal =  3.4227
gradient =

   0
   0

gradient =

  -2.61636
   0.00000

gradient =

  -2.6164
  -2.6164

jVal =   1.5777e-030
gradient =

   0
   0

gradient =

  -1.7764e-015
  0.0000e+000

gradient =

  -1.7764e-015
  -1.7764e-015

jVal =   1.5777e-030
gradient =

   0
   0

gradient =

  -1.7764e-015
  0.0000e+000

gradient =

  -1.7764e-015
  -1.7764e-015

optTheta =

   5.0000
   5.0000

functionVal =   1.5777e-030
exitFlag =  1