is case three and error ? one should specify a method/regression assumptions for such problems.
Test | Status | Code Input and Output |
---|---|---|
1 | Pass |
%%
M = [ 0.091273 0.060806
0.130562 0.076233
0.184484 0.170092
0.197685 0.244964
0.226948 0.308231
0.232963 0.309789
0.321582 0.329059
0.343480 0.384513
0.612326 0.505868
0.691264 0.529026
0.710301 0.595951
0.733409 0.637104
0.774992 0.649954
0.836475 0.717744]
x = 0.881524;
y_correct = 0.857148;
assert(abs((new_point_fit(M,x)-y_correct)/y_correct)<=0.1)
M =
0.0913 0.0608
0.1306 0.0762
0.1845 0.1701
0.1977 0.2450
0.2269 0.3082
0.2330 0.3098
0.3216 0.3291
0.3435 0.3845
0.6123 0.5059
0.6913 0.5290
0.7103 0.5960
0.7334 0.6371
0.7750 0.6500
0.8365 0.7177
|
2 | Pass |
%%
M = [ 0.016105 0.042602
0.048845 0.100409
0.135680 0.162205
0.382335 0.174843
0.409982 0.219579
0.505942 0.247533
0.535645 0.463607
0.553299 0.539963
0.562505 0.629237
0.605515 0.665519
0.609794 0.668600
0.718378 0.761209
0.803968 0.822402
0.996661 0.883440]
x = 0.999173;
y_correct = 0.954605;
assert(abs((new_point_fit(M,x)-y_correct)/y_correct)<=0.1)
M =
0.0161 0.0426
0.0488 0.1004
0.1357 0.1622
0.3823 0.1748
0.4100 0.2196
0.5059 0.2475
0.5356 0.4636
0.5533 0.5400
0.5625 0.6292
0.6055 0.6655
0.6098 0.6686
0.7184 0.7612
0.8040 0.8224
0.9967 0.8834
|
3 | Pass |
%%
M = [ 0.0705596 0.0010882
0.0880270 0.1284582
0.1557501 0.1819287
0.4294053 0.1980035
0.4354657 0.4193907
0.5222490 0.6849248
0.6131108 0.7573705
0.6277358 0.7864304
0.6678857 0.8790018]
x = 0.9916796;
y_correct = 0.7335639;
assert(abs((new_point_fit(M,x)-y_correct)/y_correct)<=0.1)
M =
0.0706 0.0011
0.0880 0.1285
0.1558 0.1819
0.4294 0.1980
0.4355 0.4194
0.5222 0.6849
0.6131 0.7574
0.6277 0.7864
0.6679 0.8790
|
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